Amr M. Kayid |
Omar ElSayed |
Sama AlShareef |
Mayar Kamali |
Zeiad Helmy |
|---|---|---|---|---|
| 37-15594 | 37-6537 | 37-705 | 37-4473 | 37-14353 |
| T10 | T10 | T10 | T10 | T10 |
What you get:
+25,000 matches +10,000 players 11 European Countries with their lead championship Seasons 2008 to 2016 Players and Teams' attributes sourced from EA Sports' FIFA video game series, including the weekly updates Team line up with squad formation (X, Y coordinates) Betting odds from up to 10 providers Detailed match events (goal types, possession, corner, cross, fouls, cards etc...) for +10,000 matches16th Oct 2016: New table containing teams' attributes from FIFA !
Original Data Source:
You can easily find data about soccer matches but they are usually scattered across different websites. A thorough data collection and processing has been done to make your life easier. I must insist that you do not make any commercial use of the data. The data was sourced from:
http://football-data.mx-api.enetscores.com/ : scores, lineup, team formation and events
http://www.football-data.co.uk/ : betting odds. Click here to understand the column naming system for betting odds:
http://sofifa.com/ : players and teams attributes from EA Sports FIFA games. FIFA series and all FIFA assets property of EA Sports.
When you have a look at the database, you will notice foreign keys for players and matches are the same as the original data sources. I have called those foreign keys "api_id".
Improving the dataset:
You will notice that some players are missing from the lineup (NULL values). This is because I have not been able to source their attributes from FIFA. This will be fixed overtime as the crawling algorithm is being improved. The dataset will also be expanded to include international games, national cups, Champion's League and Europa League. Please ask me if you're after a specific tournament.
Please get in touch with me if you want to help improve this dataset.
CLICK HERE TO ACCESS THE PROJECT GITHUB
Important note for people interested in using the crawlers: since I first wrote the crawling scripts (in python), it appears sofifa.com has changed its design and with it comes new requirements for the scripts. The existing script to crawl players ('Player Spider') will not work until i've updated it.
Exploring the data:
Now that's the fun part, there is a lot you can do with this dataset. I will be adding visuals and insights to this overview page but please have a look at the kernels and give it a try yourself ! Here are some ideas for you:
The Holy Grail... ... is obviously to predict the outcome of the game. The bookies use 3 classes (Home Win, Draw, Away Win). They get it right about 53% of the time. This is also what I've achieved so far using my own SVM. Though it may sound high for such a random sport game, you've got to know that the home team wins about 46% of the time. So the base case (constantly predicting Home Win) has indeed 46% precision.
Probabilities vs Odds
When running a multi-class classifier like SVM you could also output a probability estimate and compare it to the betting odds. Have a look at your variance vs odds and see for what games you had very different predictions.
Explore and visualize features
With access to players and teams attributes, team formations and in-game events you should be able to produce some interesting insights into The Beautiful Game . Who knows, Guardiola himself may hire one of you some day!
%reload_ext autoreload
%autoreload 2
%matplotlib inline
# import os
# os.environ["MODIN_ENGINE"] = "ray" # Modin will use Ray
# # os.environ["MODIN_ENGINE"] = "dask" # Modin will use Dask
import io
import math
import base64
import folium
import sqlite3
import warnings
import itertools
import folium.plugins
import time, datetime
import scipy
# import psycopg2
import numpy as np
import pandas as pd
# import modin.pandas as pd
import seaborn as sns
import plotly.tools as tls
import plotly.offline as py
import plotly.graph_objs as go
import matplotlib.pyplot as plt
import scipy.ndimage
from scipy import stats
from collections import *
from matplotlib.pyplot import imread
from statsmodels.stats.power import TTestIndPower
from pathlib import Path
from datetime import timedelta
from subprocess import check_output
from matplotlib import animation, rc
from mpl_toolkits.basemap import Basemap
warnings.filterwarnings("ignore")
py.init_notebook_mode(connected=True)
PATH = Path(f'data/')
from IPython.core.display import HTML
from IPython.display import display
def display_tables(table_dict):
'''
Accepts a list of IpyTable objects and returns a table which contains each IpyTable in a cell
'''
template = """<div style="float: left; padding: 10px;">
<p style='font-family:"Courier New", Courier, monospace'>
<strong>{0}</strong></p>{1}</div>"""
return HTML(
'<table><tr style="background-color:white;">' +
'\n\n'.join(['<td>' + template.format(repr(key), table._repr_html_()) +
'</td>' for key, table in table_dict.items()]) +
'</tr></table>'
)
class DataBunch:
__dfs__ = ['countries', 'leagues', 'matches', 'players',
'player_attributes', 'teams', 'team_attributes', 'sqlite_sequences']
@classmethod
def connect(cls, path):
connection = sqlite3.connect(str(path/'database.sqlite'))
return connection
def __init__(self, path):
self.path = path
self.connection = DataBunch.connect(path)
self.tables = self.get_all_tables(self.connection)
self.dfs = dict.fromkeys(DataBunch.__dfs__ , None)
self.lat_long = pd.read_excel(path/'latlong.xlsx', sheet_name="Sheet1")
self.set_tables(self.tables, self.connection)
def get_all_tables(self, connection):
cursor = connection.cursor()
cursor.execute(f"SELECT name FROM sqlite_master WHERE type='table';")
tables = cursor.fetchall()
table_names = sorted([table[0] for table in tables])
return table_names
def set_tables(self, table_names, connection):
dataframes = {}
for i, name in enumerate(table_names):
print(f'Processing {i}: {DataBunch.__dfs__[i]} dataframe | from {name} table')
dataframes[DataBunch.__dfs__[i]] = pd.read_sql_query(
f"SELECT * from {name}", connection)
for key, value in dataframes.items():
setattr(self, f'_{key}_df', value)
self.dfs[key] = value
def describe_and_check_nulls(self):
cmap = cmap=sns.diverging_palette(5, 250, as_cmap=True)
def magnify():
return [dict(selector="th",
props=[("font-size", "7pt")]),
dict(selector="td",
props=[('padding', "0em 0em")]),
dict(selector="th:hover",
props=[("font-size", "12pt")]),
dict(selector="tr:hover td:hover",
props=[('max-width', '200px'),
('font-size', '12pt')])
]
dfs_with_nulls = {}
for name, df in self.dfs.items():
print('=' * 50 + f' {name} ' + '=' * 50)
print(f'{name} INFO:')
display(df.info())
print()
print(f'{name} Describtion:')
display(df.describe().transpose())
print()
print(f'{name} Correlations:')
corr = df.corr()
display(corr.style.background_gradient(cmap, axis=1)\
.set_properties(**{'max-width': '80px', 'font-size': '10pt'})\
.set_caption("Hover to magify")\
.set_precision(2)\
.set_table_styles(magnify()))
print()
print(f'{name} NULLs:')
display(df.isnull().sum())
if df.isnull().sum().any():
print(f'Found df {name} with nulls.....')
dfs_with_nulls[name] = df
print('\n'*5)
return dfs_with_nulls
db = DataBunch(PATH)
Processing 0: countries dataframe | from Country table Processing 1: leagues dataframe | from League table Processing 2: matches dataframe | from Match table Processing 3: players dataframe | from Player table Processing 4: player_attributes dataframe | from Player_Attributes table Processing 5: teams dataframe | from Team table Processing 6: team_attributes dataframe | from Team_Attributes table Processing 7: sqlite_sequences dataframe | from sqlite_sequence table
db.__dict__.keys()
dict_keys(['path', 'connection', 'tables', 'dfs', 'lat_long', '_countries_df', '_leagues_df', '_matches_df', '_players_df', '_player_attributes_df', '_teams_df', '_team_attributes_df', '_sqlite_sequences_df'])
db.dfs.keys()
dict_keys(['countries', 'leagues', 'matches', 'players', 'player_attributes', 'teams', 'team_attributes', 'sqlite_sequences'])
display_tables(db.dfs)
'countries'
|
'leagues'
|
'matches'
25979 rows × 115 columns |
'players'
11060 rows × 7 columns |
'player_attributes'
183978 rows × 42 columns |
'teams'
299 rows × 5 columns |
'team_attributes'
1458 rows × 25 columns |
'sqlite_sequences'
|
dfs_with_nulls = db.describe_and_check_nulls()
================================================== countries ================================================== countries INFO: <class 'pandas.core.frame.DataFrame'> RangeIndex: 11 entries, 0 to 10 Data columns (total 2 columns): id 11 non-null int64 name 11 non-null object dtypes: int64(1), object(1) memory usage: 304.0+ bytes
None
countries Describtion:
| count | mean | std | min | 25% | 50% | 75% | max | |
|---|---|---|---|---|---|---|---|---|
| id | 11.0 | 12452.090909 | 8215.308472 | 1.0 | 6289.0 | 13274.0 | 18668.0 | 24558.0 |
countries Correlations:
| id | |
|---|---|
| id | 1 |
countries NULLs:
id 0 name 0 dtype: int64
================================================== leagues ================================================== leagues INFO: <class 'pandas.core.frame.DataFrame'> RangeIndex: 11 entries, 0 to 10 Data columns (total 3 columns): id 11 non-null int64 country_id 11 non-null int64 name 11 non-null object dtypes: int64(2), object(1) memory usage: 392.0+ bytes
None
leagues Describtion:
| count | mean | std | min | 25% | 50% | 75% | max | |
|---|---|---|---|---|---|---|---|---|
| id | 11.0 | 12452.090909 | 8215.308472 | 1.0 | 6289.0 | 13274.0 | 18668.0 | 24558.0 |
| country_id | 11.0 | 12452.090909 | 8215.308472 | 1.0 | 6289.0 | 13274.0 | 18668.0 | 24558.0 |
leagues Correlations:
| id | country_id | |
|---|---|---|
| id | 1 | 1 |
| country_id | 1 | 1 |
leagues NULLs:
id 0 country_id 0 name 0 dtype: int64
================================================== matches ================================================== matches INFO: <class 'pandas.core.frame.DataFrame'> RangeIndex: 25979 entries, 0 to 25978 Columns: 115 entries, id to BSA dtypes: float64(96), int64(9), object(10) memory usage: 22.8+ MB
None
matches Describtion:
| count | mean | std | min | 25% | 50% | 75% | max | |
|---|---|---|---|---|---|---|---|---|
| id | 25979.0 | 1.299000e+04 | 7499.635658 | 1.00 | 6495.50 | 12990.0 | 19484.50 | 25979.0 |
| country_id | 25979.0 | 1.173863e+04 | 7553.936759 | 1.00 | 4769.00 | 10257.0 | 17642.00 | 24558.0 |
| league_id | 25979.0 | 1.173863e+04 | 7553.936759 | 1.00 | 4769.00 | 10257.0 | 17642.00 | 24558.0 |
| stage | 25979.0 | 1.824277e+01 | 10.407354 | 1.00 | 9.00 | 18.0 | 27.00 | 38.0 |
| match_api_id | 25979.0 | 1.195429e+06 | 494627.856527 | 483129.00 | 768436.50 | 1147511.0 | 1709852.50 | 2216672.0 |
| ... | ... | ... | ... | ... | ... | ... | ... | ... |
| GBD | 14162.0 | 3.648189e+00 | 0.867440 | 1.45 | 3.20 | 3.3 | 3.75 | 11.0 |
| GBA | 14162.0 | 4.353097e+00 | 3.010189 | 1.12 | 2.50 | 3.4 | 5.00 | 34.0 |
| BSH | 14161.0 | 2.497894e+00 | 1.507793 | 1.04 | 1.67 | 2.1 | 2.62 | 17.0 |
| BSD | 14161.0 | 3.660742e+00 | 0.868272 | 1.33 | 3.25 | 3.4 | 3.75 | 13.0 |
| BSA | 14161.0 | 4.405663e+00 | 3.189814 | 1.12 | 2.50 | 3.4 | 5.00 | 34.0 |
105 rows × 8 columns
matches Correlations:
| id | country_id | league_id | stage | match_api_id | home_team_api_id | away_team_api_id | home_team_goal | away_team_goal | home_player_X1 | home_player_X2 | home_player_X3 | home_player_X4 | home_player_X5 | home_player_X6 | home_player_X7 | home_player_X8 | home_player_X9 | home_player_X10 | home_player_X11 | away_player_X1 | away_player_X2 | away_player_X3 | away_player_X4 | away_player_X5 | away_player_X6 | away_player_X7 | away_player_X8 | away_player_X9 | away_player_X10 | away_player_X11 | home_player_Y1 | home_player_Y2 | home_player_Y3 | home_player_Y4 | home_player_Y5 | home_player_Y6 | home_player_Y7 | home_player_Y8 | home_player_Y9 | home_player_Y10 | home_player_Y11 | away_player_Y1 | away_player_Y2 | away_player_Y3 | away_player_Y4 | away_player_Y5 | away_player_Y6 | away_player_Y7 | away_player_Y8 | away_player_Y9 | away_player_Y10 | away_player_Y11 | home_player_1 | home_player_2 | home_player_3 | home_player_4 | home_player_5 | home_player_6 | home_player_7 | home_player_8 | home_player_9 | home_player_10 | home_player_11 | away_player_1 | away_player_2 | away_player_3 | away_player_4 | away_player_5 | away_player_6 | away_player_7 | away_player_8 | away_player_9 | away_player_10 | away_player_11 | B365H | B365D | B365A | BWH | BWD | BWA | IWH | IWD | IWA | LBH | LBD | LBA | PSH | PSD | PSA | WHH | WHD | WHA | SJH | SJD | SJA | VCH | VCD | VCA | GBH | GBD | GBA | BSH | BSD | BSA | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| id | 1 | 0.99 | 0.99 | 0.004 | 0.13 | -0.016 | -0.016 | 0.0086 | 0.011 | -0.0034 | 0.0066 | 0.027 | -0.017 | 0.046 | -0.025 | 0.082 | -0.06 | -0.054 | 0.055 | -0.023 | 0.0061 | 0.0055 | 0.015 | -0.02 | 0.045 | -0.014 | 0.086 | -0.055 | -0.056 | 0.038 | -0.014 | -0.0032 | -0.0034 | -0.0034 | -0.01 | -0.049 | 0.069 | -0.014 | 0.1 | 0.033 | -0.054 | 0.018 | 0.0071 | nan | 0.0048 | 0.002 | -0.044 | 0.06 | -0.017 | 0.096 | 0.035 | -0.037 | 0.0076 | 0.11 | 0.14 | 0.16 | 0.17 | 0.11 | 0.15 | 0.15 | 0.13 | 0.12 | 0.14 | 0.11 | 0.1 | 0.15 | 0.16 | 0.16 | 0.11 | 0.14 | 0.14 | 0.12 | 0.12 | 0.14 | 0.11 | 0.064 | 0.1 | 0.036 | 0.061 | 0.11 | 0.041 | 0.063 | 0.096 | 0.041 | 0.07 | 0.12 | 0.045 | 0.079 | 0.12 | 0.052 | 0.066 | 0.11 | 0.044 | 0.056 | 0.098 | 0.033 | 0.075 | 0.12 | 0.056 | 0.051 | 0.095 | 0.025 | 0.049 | 0.096 | 0.024 |
| country_id | 0.99 | 1 | 1 | -0.0022 | 0.039 | -0.021 | -0.021 | 0.0081 | 0.0089 | -0.007 | -0.0021 | 0.019 | -0.018 | 0.054 | -0.05 | 0.057 | -0.048 | -0.027 | 0.038 | -0.016 | 0.0063 | -0.0025 | 0.0067 | -0.021 | 0.054 | -0.04 | 0.063 | -0.045 | -0.029 | 0.024 | -0.0098 | -0.0066 | -0.007 | -0.0031 | -0.01 | -0.056 | 0.076 | -0.0058 | 0.08 | 0.0091 | -0.041 | -5.8e-05 | 0.0072 | nan | 0.0051 | 0.002 | -0.053 | 0.068 | -0.0097 | 0.074 | 0.01 | -0.026 | -0.0086 | 0.073 | 0.1 | 0.13 | 0.13 | 0.073 | 0.11 | 0.11 | 0.091 | 0.076 | 0.1 | 0.074 | 0.07 | 0.1 | 0.13 | 0.13 | 0.068 | 0.11 | 0.11 | 0.085 | 0.076 | 0.1 | 0.077 | 0.06 | 0.093 | 0.034 | 0.057 | 0.096 | 0.038 | 0.058 | 0.082 | 0.039 | 0.064 | 0.1 | 0.038 | 0.079 | 0.12 | 0.049 | 0.06 | 0.1 | 0.039 | 0.054 | 0.09 | 0.032 | 0.069 | 0.11 | 0.05 | 0.05 | 0.088 | 0.023 | 0.048 | 0.089 | 0.022 |
| league_id | 0.99 | 1 | 1 | -0.0022 | 0.039 | -0.021 | -0.021 | 0.0081 | 0.0089 | -0.007 | -0.0021 | 0.019 | -0.018 | 0.054 | -0.05 | 0.057 | -0.048 | -0.027 | 0.038 | -0.016 | 0.0063 | -0.0025 | 0.0067 | -0.021 | 0.054 | -0.04 | 0.063 | -0.045 | -0.029 | 0.024 | -0.0098 | -0.0066 | -0.007 | -0.0031 | -0.01 | -0.056 | 0.076 | -0.0058 | 0.08 | 0.0091 | -0.041 | -5.8e-05 | 0.0072 | nan | 0.0051 | 0.002 | -0.053 | 0.068 | -0.0097 | 0.074 | 0.01 | -0.026 | -0.0086 | 0.073 | 0.1 | 0.13 | 0.13 | 0.073 | 0.11 | 0.11 | 0.091 | 0.076 | 0.1 | 0.074 | 0.07 | 0.1 | 0.13 | 0.13 | 0.068 | 0.11 | 0.11 | 0.085 | 0.076 | 0.1 | 0.077 | 0.06 | 0.093 | 0.034 | 0.057 | 0.096 | 0.038 | 0.058 | 0.082 | 0.039 | 0.064 | 0.1 | 0.038 | 0.079 | 0.12 | 0.049 | 0.06 | 0.1 | 0.039 | 0.054 | 0.09 | 0.032 | 0.069 | 0.11 | 0.05 | 0.05 | 0.088 | 0.023 | 0.048 | 0.089 | 0.022 |
| stage | 0.004 | -0.0022 | -0.0022 | 1 | 0.014 | -0.0066 | -0.0038 | 0.015 | 0.005 | 0.03 | 0.02 | 0.0014 | -0.016 | -0.0087 | -0.016 | -0.0056 | 0.0018 | 0.028 | -0.0083 | -0.0076 | 0.0057 | 0.018 | 0.0085 | -0.0074 | -0.023 | -0.013 | -0.0085 | 0.0077 | 0.034 | -0.015 | -0.003 | 0.025 | 0.034 | -0.00034 | 0.00034 | 0.019 | 0.015 | 0.0015 | -0.0021 | -0.03 | 0.0016 | -0.00021 | 0.0037 | nan | 0.0058 | 0.0067 | 0.028 | 0.0096 | 0.003 | -0.0096 | -0.028 | 0.0056 | -0.0037 | -0.0045 | 0.0076 | 0.016 | -0.0068 | 0.0084 | 0.013 | -0.0034 | 0.0096 | -2.1e-05 | 0.015 | -0.0039 | 0.0026 | 0.012 | 0.012 | 0.0017 | 0.011 | 0.013 | 0.0064 | 0.017 | 0.0048 | 0.011 | 0.0049 | 0.0072 | 0.031 | 0.0098 | 0.007 | 0.04 | 0.012 | 0.012 | 0.05 | 0.018 | 0.0073 | 0.038 | 0.014 | 0.0092 | 0.031 | 0.0038 | 0.013 | 0.032 | 0.016 | 0.005 | 0.031 | 0.012 | 0.0097 | 0.036 | 0.017 | 0.0059 | 0.033 | 0.012 | 0.0095 | 0.034 | 0.013 |
| match_api_id | 0.13 | 0.039 | 0.039 | 0.014 | 1 | 0.091 | 0.091 | 0.004 | 0.026 | 0.03 | 0.091 | 0.089 | -0.0071 | -0.067 | 0.21 | 0.21 | -0.097 | -0.25 | 0.17 | -0.05 | -0.0031 | 0.089 | 0.087 | -0.0047 | -0.074 | 0.23 | 0.2 | -0.083 | -0.25 | 0.13 | -0.028 | 0.027 | 0.031 | -0.0026 | -0.0019 | 0.059 | -0.016 | -0.03 | 0.22 | 0.23 | -0.12 | 0.16 | -0.0037 | nan | -0.0025 | -0.0008 | 0.065 | -0.028 | -0.019 | 0.21 | 0.24 | -0.094 | 0.14 | 0.39 | 0.49 | 0.41 | 0.42 | 0.46 | 0.47 | 0.44 | 0.48 | 0.49 | 0.47 | 0.44 | 0.39 | 0.49 | 0.41 | 0.43 | 0.46 | 0.47 | 0.44 | 0.48 | 0.49 | 0.47 | 0.45 | 0.046 | 0.11 | 0.0084 | 0.051 | 0.099 | 0.014 | 0.057 | 0.12 | 0.012 | 0.072 | 0.15 | 0.054 | 0.027 | 0.028 | 0.014 | 0.063 | 0.076 | 0.029 | 0.029 | 0.088 | -0.0076 | 0.068 | 0.15 | 0.045 | 0.025 | 0.11 | 0.016 | 0.027 | 0.11 | 0.013 |
| home_team_api_id | -0.016 | -0.021 | -0.021 | -0.0066 | 0.091 | 1 | 0.0057 | -0.016 | 0.016 | 0.0013 | 0.012 | 0.027 | 0.00012 | -0.0073 | 0.0052 | 0.016 | -0.0011 | -0.026 | 0.017 | 0.0028 | -0.00034 | -0.00056 | 0.0057 | -0.011 | -0.0028 | 0.021 | 0.024 | -0.00011 | -0.029 | 0.003 | 0.0088 | 0.00097 | 0.0016 | -0.0008 | -0.0011 | -0.00091 | 0.014 | 0.0013 | 0.0062 | 0.029 | -0.0072 | 0.0098 | -0.0006 | nan | -0.00018 | -0.00023 | 0.0037 | -0.0029 | -0.0084 | 0.011 | 0.032 | 0.0041 | -0.0063 | 0.043 | 0.1 | 0.066 | 0.082 | 0.055 | 0.079 | 0.069 | 0.07 | 0.095 | 0.077 | 0.076 | 0.048 | 0.062 | 0.049 | 0.069 | 0.058 | 0.055 | 0.054 | 0.045 | 0.052 | 0.063 | 0.06 | 0.045 | -0.022 | -0.036 | 0.046 | -0.02 | -0.036 | 0.041 | -0.018 | -0.038 | 0.048 | -0.022 | -0.034 | 0.052 | -0.031 | -0.044 | 0.041 | -0.021 | -0.035 | 0.024 | -0.015 | -0.02 | 0.047 | -0.019 | -0.033 | 0.018 | -0.0087 | -0.011 | 0.018 | -0.0067 | -0.011 |
| away_team_api_id | -0.016 | -0.021 | -0.021 | -0.0038 | 0.091 | 0.0057 | 1 | 0.0069 | -0.014 | 0.00099 | 0.00061 | 0.022 | 0.0043 | -0.0083 | 0.01 | 0.012 | 0.0074 | -0.025 | 0.0046 | 0.012 | -0.0028 | 0.013 | 0.018 | -0.0031 | -0.012 | 0.0093 | 0.011 | 0.012 | -0.016 | -0.012 | 0.02 | 0.00085 | 0.0011 | -0.00078 | -0.0009 | 0.0078 | 0.01 | 0.0064 | 0.0029 | 0.025 | 0.0015 | -0.0043 | -0.002 | nan | -0.0027 | -0.0025 | 0.0065 | 0.012 | 0.0086 | 0.0041 | 0.027 | 0.016 | -0.014 | 0.051 | 0.077 | 0.053 | 0.078 | 0.053 | 0.058 | 0.063 | 0.065 | 0.058 | 0.07 | 0.054 | 0.047 | 0.095 | 0.072 | 0.083 | 0.059 | 0.067 | 0.078 | 0.067 | 0.087 | 0.083 | 0.09 | -0.032 | 0.018 | 0.039 | -0.033 | 0.018 | 0.041 | -0.033 | 0.023 | 0.036 | -0.031 | 0.016 | 0.046 | -0.04 | 0.013 | 0.051 | -0.032 | 0.019 | 0.033 | -0.017 | 0.0075 | 0.016 | -0.03 | 0.019 | 0.037 | -0.012 | 0.0087 | 0.026 | -0.012 | 0.011 | 0.021 |
| home_team_goal | 0.0086 | 0.0081 | 0.0081 | 0.015 | 0.004 | -0.016 | 0.0069 | 1 | -0.064 | 0.0022 | 0.0067 | -0.0053 | -0.0066 | 0.014 | -0.0056 | 0.028 | 0.019 | -0.035 | -0.029 | 0.05 | -0.0065 | -0.018 | -0.014 | -0.016 | 0.0073 | 0.021 | -0.0047 | -0.016 | -0.00066 | 0.015 | -0.011 | 0.0013 | 0.0031 | -0.0027 | 0.00051 | -0.0075 | 0.023 | 0.00088 | -0.00046 | 0.049 | 0.043 | -0.037 | -0.0019 | nan | -0.0077 | -0.0081 | -0.0095 | -0.019 | 0.0012 | 0.017 | -0.0044 | -0.014 | 0.013 | -0.016 | -0.027 | -0.0039 | -0.011 | -0.025 | -0.01 | -0.0065 | -0.017 | -0.013 | -0.034 | -0.034 | 0.035 | 0.028 | 0.027 | 0.017 | 0.023 | 0.016 | 0.025 | 0.011 | 0.013 | 0.026 | 0.024 | -0.26 | 0.27 | 0.36 | -0.26 | 0.27 | 0.35 | -0.27 | 0.27 | 0.36 | -0.26 | 0.26 | 0.35 | -0.25 | 0.27 | 0.35 | -0.26 | 0.27 | 0.35 | -0.25 | 0.27 | 0.35 | -0.25 | 0.27 | 0.34 | -0.26 | 0.27 | 0.35 | -0.25 | 0.27 | 0.35 |
| away_team_goal | 0.011 | 0.0089 | 0.0089 | 0.005 | 0.026 | 0.016 | -0.014 | -0.064 | 1 | -0.013 | -0.022 | -0.0075 | -0.0069 | 0.01 | 0.0095 | -0.01 | -0.011 | 0.0039 | 0.012 | -0.014 | 0.015 | 0.018 | -0.0018 | -0.009 | 0.01 | -0.0028 | 0.028 | 0.023 | -0.034 | -0.037 | 0.049 | -0.011 | -0.015 | -0.0066 | -0.0047 | -0.0083 | -0.007 | 0.0091 | 0.011 | -0.0087 | -0.014 | 0.012 | 0.0081 | nan | 0.016 | 0.016 | -0.0057 | 0.023 | 0.0019 | -0.0062 | 0.045 | 0.048 | -0.04 | 0.028 | 0.029 | 0.028 | 0.025 | 0.036 | 0.037 | 0.018 | 0.022 | 0.025 | 0.026 | 0.031 | -0.013 | -0.0067 | -0.007 | -0.0065 | -0.011 | 0.0064 | 0.0047 | -0.00041 | -0.0039 | -0.022 | -0.0074 | 0.3 | -0.074 | -0.23 | 0.3 | -0.072 | -0.23 | 0.3 | -0.083 | -0.23 | 0.29 | -0.072 | -0.23 | 0.3 | -0.074 | -0.23 | 0.29 | -0.072 | -0.22 | 0.29 | -0.076 | -0.22 | 0.29 | -0.07 | -0.22 | 0.3 | -0.069 | -0.23 | 0.3 | -0.073 | -0.22 |
| home_player_X1 | -0.0034 | -0.007 | -0.007 | 0.03 | 0.03 | 0.0013 | 0.00099 | 0.0022 | -0.013 | 1 | 0.12 | 0.032 | 0.028 | -0.018 | 0.0095 | 0.013 | -0.0088 | -0.0027 | 0.0069 | -0.041 | 0.19 | 0.031 | 0.032 | 0.028 | -0.018 | 0.009 | 0.013 | -0.0049 | 0.00063 | -0.002 | nan | 0.97 | 0.96 | -4.1e-05 | -9.3e-05 | 0.026 | 0.0045 | 0.0036 | 0.03 | 0.011 | 0.0047 | -0.12 | 0.58 | nan | -4.1e-05 | -5.6e-05 | 0.019 | -0.004 | -0.0075 | 0.0084 | -0.00013 | 0.011 | nan | 0.0075 | 0.01 | 0.0089 | 0.0092 | 0.0087 | 0.009 | 0.0087 | 0.012 | 0.0086 | 0.0048 | 0.01 | 0.0099 | 0.0075 | 0.009 | 0.0085 | 0.012 | 0.011 | 0.0084 | 0.011 | 0.015 | 0.013 | 0.0077 | -0.0039 | 0.0057 | 0.0057 | -0.0031 | 0.0046 | 0.0065 | -0.0031 | 0.0054 | 0.0071 | -0.0023 | 0.0065 | 0.0069 | -0.0047 | -0.0022 | 0.0015 | -0.0027 | 0.0033 | 0.0075 | -0.0085 | 0.0035 | 0.0068 | -0.0013 | 0.0059 | 0.0073 | -0.0056 | 0.0038 | 0.0084 | -0.0064 | 0.0049 | 0.0088 |
| home_player_X2 | 0.0066 | -0.0021 | -0.0021 | 0.02 | 0.091 | 0.012 | 0.00061 | 0.0067 | -0.022 | 0.12 | 1 | 0.54 | 0.17 | -0.68 | -0.048 | 0.15 | 0.19 | 0.034 | -0.098 | 0.023 | 0.0048 | 0.13 | 0.096 | 0.0091 | -0.14 | 0.039 | 0.02 | 0.06 | -0.0058 | -0.036 | 0.009 | 0.11 | 0.11 | 0.032 | 0.027 | 0.61 | 0.24 | 0.091 | -0.047 | 0.037 | 0.092 | -0.034 | 0.017 | nan | -0.0012 | -0.0017 | 0.13 | 0.0093 | 0.033 | -0.052 | 0.012 | 0.02 | -0.011 | 0.041 | 0.0099 | 0.0095 | 0.044 | 0.049 | 0.015 | 0.015 | 0.054 | 0.029 | 0.034 | 0.019 | 0.036 | 0.03 | 0.029 | 0.025 | 0.03 | 0.028 | 0.024 | 0.028 | 0.025 | 0.036 | 0.03 | -0.021 | 0.0046 | 0.019 | -0.02 | 0.0078 | 0.025 | -0.019 | 0.013 | 0.02 | -0.019 | 0.012 | 0.027 | -0.026 | 0.011 | 0.032 | -0.018 | -0.0013 | 0.022 | -0.02 | -0.024 | -0.00043 | -0.016 | 0.0095 | 0.027 | -0.019 | -0.0099 | 0.01 | -0.019 | -0.012 | 0.0076 |
| home_player_X3 | 0.027 | 0.019 | 0.019 | 0.0014 | 0.089 | 0.027 | 0.022 | -0.0053 | -0.0075 | 0.032 | 0.54 | 1 | 0.11 | -0.51 | -0.056 | 0.14 | 0.13 | -0.047 | -0.039 | 0.0063 | 0.005 | 0.08 | 0.12 | -0.01 | -0.083 | 0.034 | 0.0056 | 0.034 | -0.02 | -0.014 | 0.01 | 0.032 | nan | -0.001 | 0.057 | 0.4 | 0.2 | 0.059 | -0.02 | 0.081 | 0.041 | 0.023 | 0.017 | nan | -0.001 | -0.0014 | 0.071 | 0.0092 | 0.033 | -0.024 | 0.02 | 0.0088 | -0.0027 | 0.034 | 0.024 | 0.02 | 0.053 | 0.052 | 0.036 | 0.028 | 0.053 | 0.04 | 0.044 | 0.022 | 0.042 | 0.043 | 0.028 | 0.023 | 0.04 | 0.039 | 0.039 | 0.03 | 0.047 | 0.031 | 0.035 | -0.012 | -0.009 | 0.002 | -0.012 | -0.0092 | 0.0063 | -0.0097 | -0.0012 | 0.0022 | -0.01 | -0.0021 | 0.012 | -0.014 | -0.016 | 0.01 | -0.011 | -0.012 | 0.0049 | -0.013 | -0.025 | -0.0072 | -0.0097 | -0.0074 | 0.0052 | -0.014 | -0.012 | 0.00092 | -0.015 | -0.014 | -0.00077 |
| home_player_X4 | -0.017 | -0.018 | -0.018 | -0.016 | -0.0071 | 0.00012 | 0.0043 | -0.0066 | -0.0069 | 0.028 | 0.17 | 0.11 | 1 | -0.57 | -0.11 | 0.1 | 0.17 | 0.056 | -0.076 | 0.052 | 0.0046 | 0.0045 | -0.021 | 0.13 | -0.11 | -0.016 | -0.005 | 0.068 | 0.026 | -0.034 | 0.024 | 0.028 | nan | -0.00071 | -0.027 | 0.52 | 0.18 | 0.046 | -0.046 | 0.022 | 0.084 | -0.037 | 0.015 | nan | -0.00071 | -0.00095 | 0.12 | 0.0065 | 0.005 | -0.045 | -0.0033 | 0.042 | -0.028 | 0.00051 | -0.016 | -0.05 | -0.026 | -0.013 | -0.022 | -0.049 | -0.0032 | -0.027 | -0.026 | -0.024 | -0.01 | -0.031 | -0.021 | -0.015 | -0.022 | -0.016 | -0.028 | -0.021 | -0.032 | -0.041 | -0.023 | -0.016 | -0.028 | -0.0065 | -0.017 | -0.024 | -0.0018 | -0.013 | -0.02 | -0.0064 | -0.016 | -0.025 | -0.0049 | -0.018 | -0.026 | 0.0041 | -0.016 | -0.028 | -0.0021 | -0.016 | -0.025 | -0.0039 | -0.016 | -0.029 | -0.0034 | -0.014 | -0.02 | -0.0013 | -0.014 | -0.022 | -0.0042 |
| home_player_X5 | 0.046 | 0.054 | 0.054 | -0.0087 | -0.067 | -0.0073 | -0.0083 | 0.014 | 0.01 | -0.018 | -0.68 | -0.51 | -0.57 | 1 | -0.092 | -0.13 | -0.28 | -0.13 | 0.16 | -0.051 | -0.0014 | -0.13 | -0.082 | -0.098 | 0.23 | -0.031 | -0.0081 | -0.12 | -0.02 | 0.061 | -0.03 | -0.018 | nan | -0.022 | -0.028 | -0.94 | -0.13 | -0.14 | 0.096 | 0.018 | -0.14 | 0.071 | -0.0084 | nan | 0.0018 | 0.0024 | -0.23 | -0.0049 | -0.036 | 0.095 | -0.0047 | -0.056 | 0.035 | -0.024 | 0.01 | 0.036 | -0.0037 | -0.02 | -0.00019 | 0.024 | -0.028 | -0.0014 | -0.0051 | 0.0082 | -0.019 | 0.0098 | 0.0088 | 0.0063 | -0.0031 | -0.004 | 0.0087 | 0.0033 | 0.0063 | 0.014 | -0.0068 | 0.00076 | 0.028 | 0.011 | -0.0027 | 0.021 | 0.0027 | -0.0025 | 0.013 | 0.01 | -0.002 | 0.019 | 0.0055 | 0.0035 | 0.025 | -0.0093 | -0.0033 | 0.029 | 0.0057 | 0.00054 | 0.042 | 0.019 | -0.0032 | 0.023 | 0.0032 | -0.00022 | 0.029 | 0.012 | 0.00082 | 0.031 | 0.016 |
| home_player_X6 | -0.025 | -0.05 | -0.05 | -0.016 | 0.21 | 0.0052 | 0.01 | -0.0056 | 0.0095 | 0.0095 | -0.048 | -0.056 | -0.11 | -0.092 | 1 | 0.27 | -0.41 | -0.41 | 0.26 | -0.19 | 0.0017 | 0.033 | 0.034 | -0.016 | -0.036 | 0.36 | 0.23 | -0.21 | -0.21 | 0.12 | -0.092 | 0.0095 | nan | 0.015 | 0.038 | 0.066 | -0.78 | -0.26 | 0.38 | 0.28 | -0.23 | 0.38 | 0.0074 | nan | -0.00097 | 0.001 | 0.028 | -0.28 | -0.21 | 0.2 | 0.17 | -0.1 | 0.2 | 0.094 | 0.11 | 0.093 | 0.096 | 0.093 | 0.061 | 0.12 | 0.13 | 0.082 | 0.13 | 0.085 | 0.092 | 0.097 | 0.094 | 0.079 | 0.089 | 0.082 | 0.089 | 0.1 | 0.094 | 0.093 | 0.081 | 0.018 | 0.013 | -0.0066 | 0.027 | 0.025 | -0.00053 | 0.024 | 0.029 | -2.4e-05 | 0.022 | 0.023 | -7.2e-05 | 0.038 | 0.008 | -0.00014 | 0.025 | 0.012 | 0.003 | -7.8e-05 | 0.0069 | -0.0039 | 0.028 | 0.032 | 0.0033 | 0.0017 | 0.0044 | -0.0024 | -0.0042 | -0.00098 | -0.014 |
| home_player_X7 | 0.082 | 0.057 | 0.057 | -0.0056 | 0.21 | 0.016 | 0.012 | 0.028 | -0.01 | 0.013 | 0.15 | 0.14 | 0.1 | -0.13 | 0.27 | 1 | -0.42 | -0.45 | 0.19 | -0.12 | 0.0052 | 0.032 | 0.035 | 0.0014 | -0.029 | 0.23 | 0.22 | -0.14 | -0.19 | 0.086 | -0.053 | 0.013 | nan | 0.019 | 0.0057 | 0.16 | -0.13 | -0.68 | 0.4 | 0.33 | -0.19 | 0.22 | 0.013 | nan | 0.0014 | 0.0045 | 0.027 | -0.16 | -0.17 | 0.15 | 0.15 | -0.073 | 0.13 | 0.099 | 0.11 | 0.089 | 0.1 | 0.096 | 0.07 | 0.073 | 0.14 | 0.08 | 0.13 | 0.066 | 0.096 | 0.097 | 0.083 | 0.08 | 0.084 | 0.088 | 0.091 | 0.092 | 0.095 | 0.094 | 0.074 | -0.03 | 0.029 | 0.024 | -0.027 | 0.035 | 0.033 | -0.025 | 0.044 | 0.033 | -0.029 | 0.037 | 0.031 | -0.038 | 0.0052 | 0.024 | -0.028 | 0.024 | 0.032 | -0.033 | 0.04 | 0.032 | -0.023 | 0.043 | 0.033 | -0.029 | 0.049 | 0.041 | -0.034 | 0.043 | 0.032 |
| home_player_X8 | -0.06 | -0.048 | -0.048 | 0.0018 | -0.097 | -0.0011 | 0.0074 | 0.019 | -0.011 | -0.0088 | 0.19 | 0.13 | 0.17 | -0.28 | -0.41 | -0.42 | 1 | -0.058 | -0.61 | 0.69 | 0.0028 | 0.048 | 0.018 | 0.052 | -0.099 | -0.21 | -0.15 | 0.32 | 0.05 | -0.19 | 0.22 | -0.0088 | nan | -0.013 | -0.0043 | 0.3 | 0.51 | 0.6 | -0.75 | 0.28 | 0.68 | -0.61 | -0.0064 | nan | 0.0064 | 0.0018 | 0.1 | 0.22 | 0.21 | -0.28 | 0.023 | 0.21 | -0.25 | -0.026 | -0.032 | -0.043 | -0.033 | -0.012 | 0.011 | -0.046 | -0.068 | 0.0051 | -0.081 | 0.029 | -0.022 | -0.031 | -0.021 | -0.022 | -0.022 | -0.021 | -0.029 | -0.038 | -0.024 | -0.033 | 0.014 | -0.027 | 0.035 | 0.057 | -0.032 | 0.026 | 0.055 | -0.031 | 0.023 | 0.053 | -0.03 | 0.025 | 0.052 | -0.022 | 0.043 | 0.041 | -0.034 | 0.043 | 0.049 | -0.019 | 0.021 | 0.049 | -0.032 | 0.027 | 0.056 | -0.025 | 0.018 | 0.051 | -0.021 | 0.026 | 0.057 |
| home_player_X9 | -0.054 | -0.027 | -0.027 | 0.028 | -0.25 | -0.026 | -0.025 | -0.035 | 0.0039 | -0.0027 | 0.034 | -0.047 | 0.056 | -0.13 | -0.41 | -0.45 | -0.058 | 1 | -0.33 | -0.3 | -0.015 | -0.0034 | -0.019 | 0.023 | -0.013 | -0.22 | -0.19 | 0.051 | 0.32 | -0.096 | -0.069 | -0.0027 | nan | 0.0071 | -0.0031 | 0.11 | 0.14 | 0.17 | -0.11 | -0.9 | 0.11 | -0.15 | -0.0084 | nan | -0.016 | -0.015 | 0.016 | 0.11 | 0.096 | -0.11 | -0.3 | 0.038 | -0.072 | -0.13 | -0.17 | -0.15 | -0.15 | -0.16 | -0.13 | -0.16 | -0.16 | -0.16 | -0.16 | -0.19 | -0.14 | -0.17 | -0.16 | -0.13 | -0.14 | -0.14 | -0.15 | -0.15 | -0.16 | -0.16 | -0.16 | 0.027 | -0.1 | -0.084 | 0.024 | -0.1 | -0.087 | 0.023 | -0.1 | -0.092 | 0.025 | -0.11 | -0.089 | 0.028 | -0.11 | -0.081 | 0.029 | -0.1 | -0.088 | 0.029 | -0.09 | -0.081 | 0.019 | -0.12 | -0.095 | 0.031 | -0.075 | -0.076 | 0.036 | -0.076 | -0.07 |
| home_player_X10 | 0.055 | 0.038 | 0.038 | -0.0083 | 0.17 | 0.017 | 0.0046 | -0.029 | 0.012 | 0.0069 | -0.098 | -0.039 | -0.076 | 0.16 | 0.26 | 0.19 | -0.61 | -0.33 | 1 | -0.63 | -0.013 | -0.029 | -0.01 | -0.029 | 0.054 | 0.14 | 0.11 | -0.21 | -0.12 | 0.22 | -0.15 | 0.0069 | nan | -0.006 | -0.0095 | -0.16 | -0.26 | -0.29 | 0.57 | 0.076 | -0.9 | 0.77 | -0.0054 | nan | -0.015 | -0.01 | -0.056 | -0.12 | -0.13 | 0.21 | 0.056 | -0.21 | 0.22 | 0.053 | 0.071 | 0.069 | 0.062 | 0.06 | 0.03 | 0.08 | 0.098 | 0.048 | 0.12 | 0.035 | 0.055 | 0.076 | 0.059 | 0.053 | 0.058 | 0.06 | 0.068 | 0.066 | 0.06 | 0.065 | 0.034 | 0.04 | -0.0032 | -0.035 | 0.046 | 0.0029 | -0.034 | 0.046 | 0.0047 | -0.031 | 0.045 | 0.0098 | -0.026 | 0.03 | 0.0057 | -0.014 | 0.047 | -0.012 | -0.026 | 0.041 | -0.0092 | -0.035 | 0.046 | 0.012 | -0.027 | 0.041 | -0.019 | -0.045 | 0.037 | -0.023 | -0.049 |
| home_player_X11 | -0.023 | -0.016 | -0.016 | -0.0076 | -0.05 | 0.0028 | 0.012 | 0.05 | -0.014 | -0.041 | 0.023 | 0.0063 | 0.052 | -0.051 | -0.19 | -0.12 | 0.69 | -0.3 | -0.63 | 1 | -0.03 | -0.012 | -0.0088 | 0.017 | -0.019 | -0.089 | -0.059 | 0.22 | -0.066 | -0.14 | 0.24 | -0.041 | nan | 0.0018 | 0.0041 | 0.059 | 0.35 | 0.39 | -0.49 | 0.54 | 0.77 | -0.77 | -0.056 | nan | -0.015 | -0.016 | 0.021 | 0.13 | 0.13 | -0.16 | 0.13 | 0.18 | -0.21 | 0.0054 | 0.025 | 0.023 | 0.017 | 0.034 | 0.051 | 0.016 | -0.019 | 0.049 | -0.043 | 0.097 | 0.024 | 0.023 | 0.036 | 0.029 | 0.028 | 0.029 | 0.026 | 0.023 | 0.039 | 0.03 | 0.067 | -0.051 | 0.091 | 0.1 | -0.054 | 0.082 | 0.1 | -0.054 | 0.074 | 0.1 | -0.053 | 0.077 | 0.096 | -0.037 | 0.088 | 0.078 | -0.059 | 0.1 | 0.095 | -0.049 | 0.086 | 0.1 | -0.052 | 0.088 | 0.1 | -0.057 | 0.078 | 0.1 | -0.055 | 0.086 | 0.11 |
| away_player_X1 | 0.0061 | 0.0063 | 0.0063 | 0.0057 | -0.0031 | -0.00034 | -0.0028 | -0.0065 | 0.015 | 0.19 | 0.0048 | 0.005 | 0.0046 | -0.0014 | 0.0017 | 0.0052 | 0.0028 | -0.015 | -0.013 | -0.03 | 1 | 0.1 | -0.0045 | -0.0038 | -0.0081 | 0.0035 | 0.002 | 0.0051 | 0.0032 | -0.0028 | nan | 0.19 | nan | -5.6e-05 | -0.00012 | 0.0031 | 0.0045 | 0.0027 | 0.0049 | -0.036 | -0.033 | -0.14 | 0.78 | nan | 0.96 | 0.86 | 0.031 | 0.027 | 0.036 | 0.033 | -0.00018 | 0.015 | nan | 0.0059 | -0.0043 | 0.013 | -0.003 | -0.0063 | -0.00093 | 0.0049 | 0.0095 | -0.0064 | -0.0052 | 0.0036 | 0.0088 | 0.0015 | 0.0044 | 0.0027 | 0.0017 | -0.0032 | -0.00099 | 0.0012 | 0.0044 | -0.00076 | 0.0098 | -0.0021 | -0.0046 | -0.003 | -0.0018 | -0.0047 | -0.0029 | -0.0022 | -0.005 | -0.0031 | -0.0012 | -0.0062 | -0.0039 | -0.0047 | -0.0022 | 0.0015 | -0.0014 | -0.0053 | -0.0033 | -0.002 | -0.0058 | -0.0035 | -0.0017 | -0.004 | -0.0028 | -0.0021 | -0.006 | -0.004 | -0.002 | -0.0061 | -0.0041 |
| away_player_X2 | 0.0055 | -0.0025 | -0.0025 | 0.018 | 0.089 | -0.00056 | 0.013 | -0.018 | 0.018 | 0.031 | 0.13 | 0.08 | 0.0045 | -0.13 | 0.033 | 0.032 | 0.048 | -0.0034 | -0.029 | -0.012 | 0.1 | 1 | 0.56 | 0.16 | -0.67 | -0.072 | 0.17 | 0.18 | 0.042 | -0.1 | 0.018 | 0.031 | nan | -0.0012 | 0.012 | 0.12 | 0.017 | 0.028 | -0.046 | -0.002 | 0.011 | -0.02 | 0.09 | nan | 0.094 | 0.098 | 0.6 | 0.27 | 0.086 | -0.039 | 0.028 | 0.089 | -0.024 | 0.033 | 0.014 | 0.016 | 0.028 | 0.019 | 0.031 | 0.019 | 0.021 | 0.033 | 0.022 | 0.025 | 0.039 | 0.021 | 1.6e-05 | 0.034 | 0.038 | 0.03 | 0.0033 | 0.043 | 0.035 | 0.028 | 0.019 | 0.026 | -0.02 | -0.026 | 0.026 | -0.018 | -0.021 | 0.028 | -0.014 | -0.024 | 0.031 | -0.014 | -0.023 | 0.037 | -0.029 | -0.033 | 0.031 | -0.025 | -0.026 | 0.0051 | -0.036 | -0.022 | 0.03 | -0.02 | -0.022 | 0.004 | -0.031 | -0.017 | 0.0032 | -0.031 | -0.017 |
| away_player_X3 | 0.015 | 0.0067 | 0.0067 | 0.0085 | 0.087 | 0.0057 | 0.018 | -0.014 | -0.0018 | 0.032 | 0.096 | 0.12 | -0.021 | -0.082 | 0.034 | 0.035 | 0.018 | -0.019 | -0.01 | -0.0088 | -0.0045 | 0.56 | 1 | 0.18 | -0.52 | -0.089 | 0.14 | 0.15 | -0.041 | -0.052 | 0.013 | 0.032 | nan | -0.00097 | 0.042 | 0.068 | 0.0047 | 0.016 | -0.0074 | 0.015 | 0.0043 | -0.004 | 0.027 | nan | -0.018 | 0.014 | 0.41 | 0.22 | 0.057 | -0.019 | 0.086 | 0.055 | 0.023 | 0.041 | 0.035 | 0.028 | 0.036 | 0.041 | 0.046 | 0.032 | 0.038 | 0.028 | 0.037 | 0.032 | 0.043 | 0.026 | 0.0089 | 0.049 | 0.047 | 0.038 | 0.023 | 0.053 | 0.041 | 0.035 | 0.024 | 0.013 | -0.024 | -0.025 | 0.014 | -0.024 | -0.022 | 0.014 | -0.019 | -0.023 | 0.016 | -0.021 | -0.022 | 0.014 | -0.034 | -0.027 | 0.015 | -0.03 | -0.026 | 0.0019 | -0.03 | -0.021 | 0.016 | -0.023 | -0.02 | 0.0038 | -0.032 | -0.024 | 0.0034 | -0.029 | -0.023 |
| away_player_X4 | -0.02 | -0.021 | -0.021 | -0.0074 | -0.0047 | -0.011 | -0.0031 | -0.016 | -0.009 | 0.028 | 0.0091 | -0.01 | 0.13 | -0.098 | -0.016 | 0.0014 | 0.052 | 0.023 | -0.029 | 0.017 | -0.0038 | 0.16 | 0.18 | 1 | -0.57 | -0.13 | 0.11 | 0.18 | 0.069 | -0.092 | 0.046 | 0.028 | nan | -0.00075 | -0.04 | 0.1 | 0.0024 | -0.013 | -0.038 | -0.0054 | 0.03 | -0.031 | 0.024 | nan | -0.015 | -0.02 | 0.53 | 0.22 | 0.048 | -0.027 | 0.021 | 0.1 | -0.04 | -0.0004 | -0.03 | -0.033 | -0.023 | -0.02 | -0.033 | -0.026 | -0.016 | -0.017 | -0.031 | -0.033 | -0.0099 | -0.035 | -0.047 | -0.021 | -0.0057 | -0.017 | -0.037 | -0.004 | -0.017 | -0.028 | -0.015 | 0.001 | -0.044 | -0.03 | 0.0046 | -0.043 | -0.031 | 0.0052 | -0.036 | -0.026 | 0.00015 | -0.045 | -0.034 | 0.0029 | -0.049 | -0.031 | 0.003 | -0.046 | -0.03 | 0.0041 | -0.032 | -0.018 | 0.0032 | -0.048 | -0.034 | 0.0047 | -0.031 | -0.019 | 0.0037 | -0.03 | -0.02 |
| away_player_X5 | 0.045 | 0.054 | 0.054 | -0.023 | -0.074 | -0.0028 | -0.012 | 0.0073 | 0.01 | -0.018 | -0.14 | -0.083 | -0.11 | 0.23 | -0.036 | -0.029 | -0.099 | -0.013 | 0.054 | -0.019 | -0.0081 | -0.67 | -0.52 | -0.57 | 1 | -0.091 | -0.13 | -0.29 | -0.14 | 0.16 | -0.042 | -0.018 | nan | 0.0019 | 0.00065 | -0.23 | -0.0059 | -0.021 | 0.079 | -0.0054 | -0.048 | 0.031 | -0.019 | nan | -0.0021 | -0.012 | -0.94 | -0.13 | -0.14 | 0.095 | 0.028 | -0.14 | 0.067 | -0.021 | 0.016 | 0.022 | 0.0031 | 0.0039 | 0.005 | 0.013 | -0.00019 | 0.0008 | 0.0085 | 0.0053 | -0.026 | 0.0091 | 0.035 | -0.006 | -0.012 | -0.012 | 0.021 | -0.026 | -0.012 | -0.0017 | -0.0052 | 0.012 | 0.018 | -0.0066 | 0.0096 | 0.011 | -0.0098 | 0.011 | 0.0026 | -0.0084 | 0.01 | 0.011 | -0.0071 | 0.004 | 0.03 | -0.0033 | 0.0079 | 0.021 | -0.0071 | 0.021 | 0.024 | -0.009 | 0.0064 | 0.018 | -0.0071 | 0.02 | 0.013 | -0.015 | 0.02 | 0.014 | -0.011 |
| away_player_X6 | -0.014 | -0.04 | -0.04 | -0.013 | 0.23 | 0.021 | 0.0093 | 0.021 | -0.0028 | 0.009 | 0.039 | 0.034 | -0.016 | -0.031 | 0.36 | 0.23 | -0.21 | -0.22 | 0.14 | -0.089 | 0.0035 | -0.072 | -0.089 | -0.13 | -0.091 | 1 | 0.23 | -0.39 | -0.39 | 0.22 | -0.18 | 0.009 | nan | 0.009 | 0.014 | 0.029 | -0.27 | -0.2 | 0.2 | 0.18 | -0.11 | 0.19 | 0.013 | nan | -0.00098 | 0.0054 | 0.058 | -0.8 | -0.24 | 0.38 | 0.26 | -0.2 | 0.36 | 0.09 | 0.093 | 0.084 | 0.087 | 0.088 | 0.082 | 0.089 | 0.11 | 0.093 | 0.097 | 0.078 | 0.1 | 0.11 | 0.097 | 0.093 | 0.1 | 0.063 | 0.13 | 0.12 | 0.094 | 0.13 | 0.087 | -0.021 | 0.039 | 0.032 | -0.016 | 0.053 | 0.041 | -0.016 | 0.055 | 0.038 | -0.017 | 0.051 | 0.04 | -0.049 | 0.05 | 0.075 | -0.015 | 0.039 | 0.041 | -0.018 | 0.029 | 0.022 | -0.013 | 0.06 | 0.047 | -0.0083 | 0.027 | 0.018 | -0.011 | 0.022 | 0.00056 |
| away_player_X7 | 0.086 | 0.063 | 0.063 | -0.0085 | 0.2 | 0.024 | 0.011 | -0.0047 | 0.028 | 0.013 | 0.02 | 0.0056 | -0.005 | -0.0081 | 0.23 | 0.22 | -0.15 | -0.19 | 0.11 | -0.059 | 0.002 | 0.17 | 0.14 | 0.11 | -0.13 | 0.23 | 1 | -0.39 | -0.44 | 0.1 | -0.081 | 0.013 | nan | -0.016 | -0.0044 | 0.0064 | -0.17 | -0.18 | 0.15 | 0.15 | -0.098 | 0.13 | 0.0026 | nan | 0.0015 | -0.00059 | 0.15 | -0.097 | -0.7 | 0.4 | 0.34 | -0.12 | 0.18 | 0.089 | 0.095 | 0.082 | 0.087 | 0.079 | 0.078 | 0.092 | 0.086 | 0.081 | 0.096 | 0.072 | 0.092 | 0.1 | 0.079 | 0.097 | 0.089 | 0.076 | 0.068 | 0.13 | 0.083 | 0.12 | 0.073 | 0.028 | -0.011 | -0.043 | 0.034 | -0.0056 | -0.033 | 0.037 | -0.001 | -0.037 | 0.034 | -0.0079 | -0.04 | 0.0078 | -0.023 | -0.03 | 0.034 | -0.016 | -0.038 | 0.03 | 0.0018 | -0.033 | 0.034 | 0.0044 | -0.029 | 0.041 | -0.0039 | -0.038 | 0.038 | -0.008 | -0.054 |
| away_player_X8 | -0.055 | -0.045 | -0.045 | 0.0077 | -0.083 | -0.00011 | 0.012 | -0.016 | 0.023 | -0.0049 | 0.06 | 0.034 | 0.068 | -0.12 | -0.21 | -0.14 | 0.32 | 0.051 | -0.21 | 0.22 | 0.0051 | 0.18 | 0.15 | 0.18 | -0.29 | -0.39 | -0.39 | 1 | -0.068 | -0.59 | 0.69 | -0.0049 | nan | -0.0049 | -0.0076 | 0.12 | 0.22 | 0.2 | -0.27 | 0.023 | 0.22 | -0.25 | 0.00026 | nan | 0.0065 | 0.0053 | 0.31 | 0.51 | 0.6 | -0.75 | 0.29 | 0.67 | -0.62 | -0.013 | -0.024 | -0.017 | -0.027 | -0.014 | -0.0025 | -0.028 | -0.024 | -0.012 | -0.027 | 0.01 | -0.021 | -0.023 | -0.028 | -0.025 | -0.017 | 0.0077 | -0.04 | -0.059 | 0.011 | -0.082 | 0.04 | 0.061 | -0.02 | -0.037 | 0.058 | -0.03 | -0.042 | 0.057 | -0.03 | -0.038 | 0.053 | -0.03 | -0.037 | 0.063 | -0.02 | -0.044 | 0.053 | -0.013 | -0.045 | 0.059 | -0.03 | -0.038 | 0.057 | -0.032 | -0.042 | 0.056 | -0.027 | -0.032 | 0.058 | -0.022 | -0.023 |
| away_player_X9 | -0.056 | -0.029 | -0.029 | 0.034 | -0.25 | -0.029 | -0.016 | -0.00066 | -0.034 | 0.00063 | -0.0058 | -0.02 | 0.026 | -0.02 | -0.21 | -0.19 | 0.05 | 0.32 | -0.12 | -0.066 | 0.0032 | 0.042 | -0.041 | 0.069 | -0.14 | -0.39 | -0.44 | -0.068 | 1 | -0.29 | -0.31 | 0.00063 | nan | 0.00063 | -0.0045 | 0.028 | 0.11 | 0.1 | -0.094 | -0.3 | 0.053 | -0.078 | 0.0032 | nan | nan | 0.00063 | 0.13 | 0.13 | 0.16 | -0.12 | -0.9 | 0.082 | -0.13 | -0.13 | -0.16 | -0.15 | -0.14 | -0.14 | -0.15 | -0.15 | -0.15 | -0.15 | -0.15 | -0.15 | -0.13 | -0.17 | -0.16 | -0.14 | -0.16 | -0.13 | -0.16 | -0.16 | -0.16 | -0.15 | -0.18 | -0.074 | -0.034 | 0.03 | -0.078 | -0.034 | 0.025 | -0.081 | -0.034 | 0.022 | -0.074 | -0.033 | 0.023 | -0.061 | -0.021 | 0.031 | -0.075 | -0.034 | 0.029 | -0.069 | -0.035 | 0.021 | -0.079 | -0.052 | 0.015 | -0.074 | -0.028 | 0.022 | -0.071 | -0.026 | 0.031 |
| away_player_X10 | 0.038 | 0.024 | 0.024 | -0.015 | 0.13 | 0.003 | -0.012 | 0.015 | -0.037 | -0.002 | -0.036 | -0.014 | -0.034 | 0.061 | 0.12 | 0.086 | -0.19 | -0.096 | 0.22 | -0.14 | -0.0028 | -0.1 | -0.052 | -0.092 | 0.16 | 0.22 | 0.1 | -0.59 | -0.29 | 1 | -0.63 | -0.002 | nan | 0.011 | 0.0068 | -0.061 | -0.11 | -0.1 | 0.18 | 0.039 | -0.21 | 0.21 | -0.0028 | nan | nan | -0.0062 | -0.17 | -0.26 | -0.25 | 0.53 | 0.029 | -0.9 | 0.79 | 0.029 | 0.042 | 0.035 | 0.041 | 0.034 | 0.037 | 0.048 | 0.039 | 0.036 | 0.037 | 0.011 | 0.028 | 0.054 | 0.049 | 0.036 | 0.05 | 0.024 | 0.069 | 0.076 | 0.019 | 0.1 | 0.01 | -0.056 | 0.051 | 0.072 | -0.055 | 0.057 | 0.073 | -0.053 | 0.06 | 0.073 | -0.051 | 0.059 | 0.072 | -0.047 | 0.036 | 0.05 | -0.049 | 0.043 | 0.075 | -0.059 | 0.056 | 0.081 | -0.05 | 0.062 | 0.074 | -0.065 | 0.058 | 0.082 | -0.066 | 0.056 | 0.082 |
| away_player_X11 | -0.014 | -0.0098 | -0.0098 | -0.003 | -0.028 | 0.0088 | 0.02 | -0.011 | 0.049 | nan | 0.009 | 0.01 | 0.024 | -0.03 | -0.092 | -0.053 | 0.22 | -0.069 | -0.15 | 0.24 | nan | 0.018 | 0.013 | 0.046 | -0.042 | -0.18 | -0.081 | 0.69 | -0.31 | -0.63 | 1 | nan | nan | -0.0065 | -0.0069 | 0.026 | 0.14 | 0.13 | -0.16 | 0.14 | 0.19 | -0.21 | nan | nan | nan | 0.002 | 0.058 | 0.36 | 0.38 | -0.48 | 0.56 | 0.78 | -0.81 | 0.033 | 0.044 | 0.048 | 0.029 | 0.046 | 0.045 | 0.031 | 0.034 | 0.047 | 0.036 | 0.073 | 0.022 | 0.04 | 0.041 | 0.023 | 0.041 | 0.05 | 0.017 | -0.0057 | 0.067 | -0.038 | 0.11 | 0.11 | -0.0086 | -0.073 | 0.11 | -0.018 | -0.076 | 0.11 | -0.025 | -0.072 | 0.1 | -0.022 | -0.071 | 0.097 | -0.0021 | -0.06 | 0.1 | 0.002 | -0.078 | 0.11 | -0.02 | -0.079 | 0.11 | -0.012 | -0.07 | 0.12 | -0.027 | -0.087 | 0.12 | -0.023 | -0.084 |
| home_player_Y1 | -0.0032 | -0.0066 | -0.0066 | 0.025 | 0.027 | 0.00097 | 0.00085 | 0.0013 | -0.011 | 0.97 | 0.11 | 0.032 | 0.028 | -0.018 | 0.0095 | 0.013 | -0.0088 | -0.0027 | 0.0069 | -0.041 | 0.19 | 0.031 | 0.032 | 0.028 | -0.018 | 0.009 | 0.013 | -0.0049 | 0.00063 | -0.002 | nan | 1 | 0.86 | -4.1e-05 | -9.3e-05 | 0.026 | 0.0045 | 0.0036 | 0.03 | 0.011 | 0.0047 | -0.12 | 0.58 | nan | -4.1e-05 | -5.6e-05 | 0.019 | -0.004 | -0.0075 | 0.0084 | -0.00013 | 0.011 | nan | 0.006 | 0.0085 | 0.0081 | 0.007 | 0.0065 | 0.007 | 0.0072 | 0.011 | 0.0064 | 0.0037 | 0.01 | 0.011 | 0.0057 | 0.0072 | 0.0066 | 0.0098 | 0.0088 | 0.0066 | 0.011 | 0.015 | 0.012 | 0.0058 | -0.0043 | 0.0045 | 0.0053 | -0.0037 | 0.0038 | 0.0061 | -0.0036 | 0.0043 | 0.0063 | -0.0028 | 0.005 | 0.0059 | -0.0047 | -0.0022 | 0.0015 | -0.0033 | 0.0025 | 0.007 | -0.0086 | 0.0027 | 0.0063 | -0.002 | 0.0051 | 0.0068 | -0.0062 | 0.0032 | 0.0079 | -0.0068 | 0.004 | 0.0081 |
| home_player_Y2 | -0.0034 | -0.007 | -0.007 | 0.034 | 0.031 | 0.0016 | 0.0011 | 0.0031 | -0.015 | 0.96 | 0.11 | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | 0.86 | 1 | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | 0.0087 | 0.011 | 0.0089 | 0.011 | 0.011 | 0.011 | 0.0097 | 0.011 | 0.01 | 0.0058 | 0.0092 | 0.0078 | 0.0091 | 0.01 | 0.01 | 0.013 | 0.013 | 0.0098 | 0.0099 | 0.013 | 0.012 | 0.0092 | -0.003 | 0.0065 | 0.0058 | -0.0022 | 0.0052 | 0.0064 | -0.0023 | 0.0061 | 0.0075 | -0.0015 | 0.0077 | 0.0076 | nan | nan | nan | -0.0019 | 0.004 | 0.0076 | -0.0076 | 0.0043 | 0.0068 | -0.00033 | 0.0064 | 0.0074 | -0.0045 | 0.0043 | 0.0082 | -0.0054 | 0.0056 | 0.0089 |
| home_player_Y3 | -0.0034 | -0.0031 | -0.0031 | -0.00034 | -0.0026 | -0.0008 | -0.00078 | -0.0027 | -0.0066 | -4.1e-05 | 0.032 | -0.001 | -0.00071 | -0.022 | 0.015 | 0.019 | -0.013 | 0.0071 | -0.006 | 0.0018 | -5.6e-05 | -0.0012 | -0.00097 | -0.00075 | 0.0019 | 0.009 | -0.016 | -0.0049 | 0.00063 | 0.011 | -0.0065 | -4.1e-05 | nan | 1 | 0.45 | -0.0016 | -0.03 | -0.04 | -0.0026 | -0.0059 | 0.0047 | -0.0056 | -7.2e-05 | nan | -4.1e-05 | -5.6e-05 | -0.0017 | -0.013 | 0.0035 | -0.0027 | -0.0058 | -0.013 | 0.007 | 0.0075 | -0.0055 | -0.004 | -0.0036 | 0.011 | 0.0026 | -0.0038 | 0.0075 | 0.0042 | -0.0051 | -0.004 | -0.0036 | -0.0046 | -0.004 | -2.9e-05 | -0.0037 | -0.0038 | -0.0036 | -0.0049 | -0.0041 | -0.0046 | -0.00058 | -0.0022 | -0.0027 | -0.0019 | -0.0017 | -0.0023 | -0.0018 | -0.0022 | -0.0026 | -0.002 | -0.002 | -0.0021 | -0.0018 | nan | nan | nan | -0.0015 | -0.0029 | -0.0022 | -0.0024 | -0.002 | -0.0024 | -0.0018 | -0.0027 | -0.0017 | -0.0023 | -0.0039 | -0.0027 | -0.0026 | -0.0026 | -0.0024 |
| home_player_Y4 | -0.01 | -0.01 | -0.01 | 0.00034 | -0.0019 | -0.0011 | -0.0009 | 0.00051 | -0.0047 | -9.3e-05 | 0.027 | 0.057 | -0.027 | -0.028 | 0.038 | 0.0057 | -0.0043 | -0.0031 | -0.0095 | 0.0041 | -0.00012 | 0.012 | 0.042 | -0.04 | 0.00065 | 0.014 | -0.0044 | -0.0076 | -0.0045 | 0.0068 | -0.0069 | -9.3e-05 | nan | 0.45 | 1 | -0.0036 | -0.068 | -0.012 | 0.014 | -0.0029 | 0.016 | 0.01 | -0.00016 | nan | -9.3e-05 | -0.00012 | -0.0037 | -0.0089 | 0.0029 | 0.0088 | 0.0023 | -0.018 | 0.01 | -0.00016 | -0.01 | 0.0042 | -0.0059 | 0.0081 | -0.0056 | -0.0089 | 0.002 | 0.002 | -0.00026 | 5.3e-05 | -0.001 | 0.00018 | -0.0089 | 9.4e-05 | 0.0036 | -0.0053 | -0.0021 | -0.0024 | -0.00033 | -0.00036 | -0.00092 | -0.0072 | -0.00058 | 0.0042 | -0.0071 | 0.00042 | 0.006 | -0.0076 | 0.0011 | 0.0043 | -0.0071 | -0.00054 | 0.0045 | -0.0083 | 0.0041 | 0.014 | -0.0067 | -0.00029 | 0.0045 | -0.0082 | 1.3e-05 | 0.0049 | -0.0066 | -0.00068 | 0.0061 | -0.0046 | -0.0068 | -0.0036 | -0.0046 | -0.0056 | -0.0039 |
| home_player_Y5 | -0.049 | -0.056 | -0.056 | 0.019 | 0.059 | -0.00091 | 0.0078 | -0.0075 | -0.0083 | 0.026 | 0.61 | 0.4 | 0.52 | -0.94 | 0.066 | 0.16 | 0.3 | 0.11 | -0.16 | 0.059 | 0.0031 | 0.12 | 0.068 | 0.1 | -0.23 | 0.029 | 0.0064 | 0.12 | 0.028 | -0.061 | 0.026 | 0.026 | nan | -0.0016 | -0.0036 | 1 | 0.16 | 0.14 | -0.098 | 0.0025 | 0.16 | -0.066 | 0.013 | nan | -0.0016 | -0.0022 | 0.23 | 0.0009 | 0.031 | -0.098 | -0.002 | 0.056 | -0.032 | 0.021 | -0.015 | -0.051 | -0.0087 | 0.006 | -0.0089 | -0.035 | 0.024 | -0.0075 | -0.0034 | -0.014 | 0.012 | -0.018 | -0.019 | -0.016 | -0.0084 | -0.0048 | -0.017 | -0.012 | -0.02 | -0.025 | -0.0043 | -0.01 | -0.024 | -0.0034 | -0.0073 | -0.016 | 0.0056 | -0.0076 | -0.0074 | -0.0017 | -0.008 | -0.015 | 0.0016 | -0.014 | -0.023 | 0.014 | -0.0061 | -0.024 | 0.0022 | -0.0086 | -0.034 | -0.0097 | -0.0066 | -0.02 | 0.0038 | -0.0065 | -0.02 | -0.003 | -0.007 | -0.023 | -0.0065 |
| home_player_Y6 | 0.069 | 0.076 | 0.076 | 0.015 | -0.016 | 0.014 | 0.01 | 0.023 | -0.007 | 0.0045 | 0.24 | 0.2 | 0.18 | -0.13 | -0.78 | -0.13 | 0.51 | 0.14 | -0.26 | 0.35 | 0.0045 | 0.017 | 0.0047 | 0.0024 | -0.0059 | -0.27 | -0.17 | 0.22 | 0.11 | -0.11 | 0.14 | 0.0045 | nan | -0.03 | -0.068 | 0.16 | 1 | 0.52 | -0.18 | 0.047 | 0.29 | -0.4 | 0.0029 | nan | 0.0045 | 0.0022 | 0.0056 | 0.31 | 0.25 | -0.14 | -0.057 | 0.12 | -0.2 | -0.00048 | 0.0081 | -0.0013 | 0.01 | 0.018 | 0.041 | -0.0061 | -0.0061 | 0.031 | -0.024 | 0.044 | 0.0076 | 0.021 | 0.019 | 0.019 | 0.022 | 0.023 | 0.014 | 0.0054 | 0.012 | 0.017 | 0.033 | -0.018 | 0.047 | 0.039 | -0.025 | 0.033 | 0.035 | -0.02 | 0.027 | 0.033 | -0.017 | 0.045 | 0.041 | -0.051 | 0.039 | 0.044 | -0.023 | 0.046 | 0.035 | -0.0017 | 0.039 | 0.029 | -0.022 | 0.038 | 0.038 | -0.00091 | 0.04 | 0.022 | 0.0039 | 0.046 | 0.033 |
| home_player_Y7 | -0.014 | -0.0058 | -0.0058 | 0.0015 | -0.03 | 0.0013 | 0.0064 | 0.00088 | 0.0091 | 0.0036 | 0.091 | 0.059 | 0.046 | -0.14 | -0.26 | -0.68 | 0.6 | 0.17 | -0.29 | 0.39 | 0.0027 | 0.028 | 0.016 | -0.013 | -0.021 | -0.2 | -0.18 | 0.2 | 0.1 | -0.1 | 0.13 | 0.0036 | nan | -0.04 | -0.012 | 0.14 | 0.52 | 1 | -0.21 | 0.05 | 0.36 | -0.34 | -0.00011 | nan | 0.0036 | -8.2e-05 | 0.017 | 0.23 | 0.26 | -0.12 | -0.046 | 0.11 | -0.17 | -0.0099 | -0.001 | -0.0023 | -0.00067 | 0.016 | 0.04 | 0.027 | -0.026 | 0.033 | -0.036 | 0.053 | 0.0078 | 0.011 | 0.025 | 0.013 | 0.024 | 0.021 | 0.013 | 0.0069 | 0.0091 | 0.015 | 0.037 | 0.016 | 0.042 | 0.024 | 0.012 | 0.03 | 0.016 | 0.014 | 0.018 | 0.014 | 0.018 | 0.037 | 0.023 | 0.013 | 0.049 | 0.03 | 0.013 | 0.044 | 0.019 | 0.02 | 0.016 | 0.0047 | 0.012 | 0.035 | 0.023 | 0.017 | 0.01 | -0.0061 | 0.021 | 0.017 | 0.0037 |
| home_player_Y8 | 0.1 | 0.08 | 0.08 | -0.0021 | 0.22 | 0.0062 | 0.0029 | -0.00046 | 0.011 | 0.03 | -0.047 | -0.02 | -0.046 | 0.096 | 0.38 | 0.4 | -0.75 | -0.11 | 0.57 | -0.49 | 0.0049 | -0.046 | -0.0074 | -0.038 | 0.079 | 0.2 | 0.15 | -0.27 | -0.094 | 0.18 | -0.16 | 0.03 | nan | -0.0026 | 0.014 | -0.098 | -0.18 | -0.21 | 1 | -0.0028 | -0.57 | 0.56 | 0.021 | nan | -0.0026 | 0.0014 | -0.086 | -0.14 | -0.12 | 0.32 | 0.044 | -0.18 | 0.22 | 0.083 | 0.11 | 0.1 | 0.099 | 0.087 | 0.064 | 0.11 | 0.14 | 0.078 | 0.14 | 0.058 | 0.085 | 0.11 | 0.089 | 0.084 | 0.097 | 0.094 | 0.098 | 0.11 | 0.094 | 0.099 | 0.066 | 0.017 | 0.025 | -0.017 | 0.022 | 0.028 | -0.015 | 0.022 | 0.028 | -0.015 | 0.023 | 0.038 | -0.0069 | 0.00087 | -0.002 | 0.003 | 0.023 | 0.016 | -0.0062 | 0.014 | 0.026 | -0.02 | 0.026 | 0.037 | -0.0097 | 0.021 | 0.03 | -0.027 | 0.018 | 0.025 | -0.031 |
| home_player_Y9 | 0.033 | 0.0091 | 0.0091 | -0.03 | 0.23 | 0.029 | 0.025 | 0.049 | -0.0087 | 0.011 | 0.037 | 0.081 | 0.022 | 0.018 | 0.28 | 0.33 | 0.28 | -0.9 | 0.076 | 0.54 | -0.036 | -0.002 | 0.015 | -0.0054 | -0.0054 | 0.18 | 0.15 | 0.023 | -0.3 | 0.039 | 0.14 | 0.011 | nan | -0.0059 | -0.0029 | 0.0025 | 0.047 | 0.05 | -0.0028 | 1 | 0.18 | -0.092 | -0.017 | nan | -0.04 | -0.036 | 0.0027 | -0.059 | -0.04 | 0.048 | 0.31 | 0.029 | 0.00032 | 0.12 | 0.17 | 0.14 | 0.14 | 0.15 | 0.14 | 0.15 | 0.15 | 0.16 | 0.13 | 0.2 | 0.14 | 0.16 | 0.16 | 0.13 | 0.15 | 0.14 | 0.15 | 0.15 | 0.16 | 0.15 | 0.16 | -0.039 | 0.12 | 0.1 | -0.038 | 0.11 | 0.1 | -0.036 | 0.11 | 0.11 | -0.037 | 0.12 | 0.1 | -0.038 | 0.11 | 0.093 | -0.043 | 0.12 | 0.1 | -0.039 | 0.1 | 0.096 | -0.032 | 0.13 | 0.11 | -0.043 | 0.088 | 0.092 | -0.047 | 0.091 | 0.087 |
| home_player_Y10 | -0.054 | -0.041 | -0.041 | 0.0016 | -0.12 | -0.0072 | 0.0015 | 0.043 | -0.014 | 0.0047 | 0.092 | 0.041 | 0.084 | -0.14 | -0.23 | -0.19 | 0.68 | 0.11 | -0.9 | 0.77 | -0.033 | 0.011 | 0.0043 | 0.03 | -0.048 | -0.11 | -0.098 | 0.22 | 0.053 | -0.21 | 0.19 | 0.0047 | nan | 0.0047 | 0.016 | 0.16 | 0.29 | 0.36 | -0.57 | 0.18 | 1 | -0.81 | -0.013 | nan | -0.037 | -0.037 | 0.05 | 0.12 | 0.13 | -0.2 | 0.015 | 0.22 | -0.23 | -0.032 | -0.039 | -0.037 | -0.035 | -0.026 | -0.0034 | -0.048 | -0.067 | -0.015 | -0.096 | 0.017 | -0.021 | -0.039 | -0.021 | -0.021 | -0.021 | -0.027 | -0.034 | -0.033 | -0.023 | -0.032 | 0.0039 | -0.056 | 0.035 | 0.064 | -0.06 | 0.027 | 0.063 | -0.06 | 0.024 | 0.063 | -0.06 | 0.02 | 0.056 | -0.047 | 0.031 | 0.045 | -0.064 | 0.046 | 0.054 | -0.052 | 0.038 | 0.062 | -0.06 | 0.023 | 0.058 | -0.054 | 0.039 | 0.068 | -0.051 | 0.045 | 0.071 |
| home_player_Y11 | 0.018 | -5.8e-05 | -5.8e-05 | -0.00021 | 0.16 | 0.0098 | -0.0043 | -0.037 | 0.012 | -0.12 | -0.034 | 0.023 | -0.037 | 0.071 | 0.38 | 0.22 | -0.61 | -0.15 | 0.77 | -0.77 | -0.14 | -0.02 | -0.004 | -0.031 | 0.031 | 0.19 | 0.13 | -0.25 | -0.078 | 0.21 | -0.21 | -0.12 | nan | -0.0056 | 0.01 | -0.066 | -0.4 | -0.34 | 0.56 | -0.092 | -0.81 | 1 | -0.19 | nan | -0.095 | -0.081 | -0.034 | -0.19 | -0.18 | 0.22 | 0.009 | -0.22 | 0.27 | 0.043 | 0.045 | 0.033 | 0.041 | 0.032 | -0.0028 | 0.049 | 0.076 | 0.016 | 0.1 | -0.021 | 0.024 | 0.043 | 0.028 | 0.017 | 0.024 | 0.029 | 0.036 | 0.032 | 0.022 | 0.032 | -0.0036 | 0.039 | -0.047 | -0.07 | 0.044 | -0.038 | -0.066 | 0.045 | -0.03 | -0.066 | 0.043 | -0.03 | -0.06 | 0.034 | -0.052 | -0.055 | 0.048 | -0.058 | -0.058 | 0.029 | -0.047 | -0.065 | 0.045 | -0.034 | -0.064 | 0.038 | -0.042 | -0.064 | 0.034 | -0.048 | -0.069 |
| away_player_Y1 | 0.0071 | 0.0072 | 0.0072 | 0.0037 | -0.0037 | -0.0006 | -0.002 | -0.0019 | 0.0081 | 0.58 | 0.017 | 0.017 | 0.015 | -0.0084 | 0.0074 | 0.013 | -0.0064 | -0.0084 | -0.0054 | -0.056 | 0.78 | 0.09 | 0.027 | 0.024 | -0.019 | 0.013 | 0.0026 | 0.00026 | 0.0032 | -0.0028 | nan | 0.58 | nan | -7.2e-05 | -0.00016 | 0.013 | 0.0029 | -0.00011 | 0.021 | -0.017 | -0.013 | -0.19 | 1 | nan | 0.58 | 0.52 | 0.036 | 0.013 | 0.025 | 0.027 | -0.00018 | 0.015 | nan | 0.00073 | -0.0043 | 0.0067 | -0.0057 | -0.0079 | -0.0022 | 0.0049 | 0.0061 | -0.0077 | -0.0052 | 0.0025 | 0.012 | -0.0028 | -0.00056 | -0.0017 | -0.0021 | -0.0019 | -0.002 | 0.0051 | 0.0048 | -0.00076 | 0.0021 | -0.0041 | -0.0049 | -0.0021 | -0.004 | -0.0043 | -0.0018 | -0.0038 | -0.005 | -0.0029 | -0.0031 | -0.0062 | -0.0035 | -0.0047 | -0.0022 | 0.0015 | -0.0033 | -0.0053 | -0.0023 | -0.0043 | -0.0057 | -0.0026 | -0.0036 | -0.0038 | -0.0018 | -0.0048 | -0.0057 | -0.0023 | -0.0045 | -0.0056 | -0.0029 |
| away_player_Y2 | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan |
| away_player_Y3 | 0.0048 | 0.0051 | 0.0051 | 0.0058 | -0.0025 | -0.00018 | -0.0027 | -0.0077 | 0.016 | -4.1e-05 | -0.0012 | -0.001 | -0.00071 | 0.0018 | -0.00097 | 0.0014 | 0.0064 | -0.016 | -0.015 | -0.015 | 0.96 | 0.094 | -0.018 | -0.015 | -0.0021 | -0.00098 | 0.0015 | 0.0065 | nan | nan | nan | -4.1e-05 | nan | -4.1e-05 | -9.3e-05 | -0.0016 | 0.0045 | 0.0036 | -0.0026 | -0.04 | -0.037 | -0.095 | 0.58 | nan | 1 | 0.89 | 0.025 | 0.03 | 0.036 | 0.031 | nan | nan | nan | 0.0074 | nan | 0.013 | -0.0014 | -0.0047 | -0.00026 | nan | 0.0097 | -0.005 | -0.0044 | 0.0036 | 0.0064 | 0.0032 | 0.006 | 0.0042 | 0.003 | -0.0033 | -0.00042 | -0.00063 | 0.0036 | nan | 0.012 | -0.00095 | -0.0038 | -0.003 | -0.00067 | -0.0042 | -0.003 | -0.0013 | -0.0043 | -0.0027 | -0.00017 | -0.0054 | -0.0035 | nan | nan | nan | -0.00034 | -0.0047 | -0.0033 | -0.00079 | -0.0051 | -0.0035 | -0.00061 | -0.0035 | -0.0029 | -0.00059 | -0.0054 | -0.0041 | -0.0007 | -0.0055 | -0.0041 |
| away_player_Y4 | 0.002 | 0.002 | 0.002 | 0.0067 | -0.0008 | -0.00023 | -0.0025 | -0.0081 | 0.016 | -5.6e-05 | -0.0017 | -0.0014 | -0.00095 | 0.0024 | 0.001 | 0.0045 | 0.0018 | -0.015 | -0.01 | -0.016 | 0.86 | 0.098 | 0.014 | -0.02 | -0.012 | 0.0054 | -0.00059 | 0.0053 | 0.00063 | -0.0062 | 0.002 | -5.6e-05 | nan | -5.6e-05 | -0.00012 | -0.0022 | 0.0022 | -8.2e-05 | 0.0014 | -0.036 | -0.037 | -0.081 | 0.52 | nan | 0.89 | 1 | 0.022 | 0.014 | 0.034 | 0.036 | -0.0058 | 0.011 | 0.007 | 0.0054 | 0.0086 | 0.011 | 0.0015 | -0.006 | 0.0061 | -0.0031 | 0.0067 | -0.00075 | -0.0043 | 0.0033 | 0.0087 | 0.0011 | 0.0039 | 0.0062 | 0.0076 | -0.00019 | 0.0011 | -0.0024 | 0.005 | 0.0035 | 0.0085 | -0.00023 | -0.0057 | -0.0044 | -7.3e-05 | -0.0057 | -0.0043 | -0.00045 | -0.0057 | -0.0042 | 0.0005 | -0.0067 | -0.0048 | 0.0014 | -0.0063 | -0.005 | 0.00022 | -0.0056 | -0.0046 | 0.00018 | -0.0072 | -0.0052 | 0.00011 | -0.0048 | -0.0042 | -0.00059 | -0.0054 | -0.0041 | -0.0007 | -0.0055 | -0.0041 |
| away_player_Y5 | -0.044 | -0.053 | -0.053 | 0.028 | 0.065 | 0.0037 | 0.0065 | -0.0095 | -0.0057 | 0.019 | 0.13 | 0.071 | 0.12 | -0.23 | 0.028 | 0.027 | 0.1 | 0.016 | -0.056 | 0.021 | 0.031 | 0.6 | 0.41 | 0.53 | -0.94 | 0.058 | 0.15 | 0.31 | 0.13 | -0.17 | 0.058 | 0.019 | nan | -0.0017 | -0.0037 | 0.23 | 0.0056 | 0.017 | -0.086 | 0.0027 | 0.05 | -0.034 | 0.036 | nan | 0.025 | 0.022 | 1 | 0.17 | 0.14 | -0.099 | -0.0026 | 0.16 | -0.066 | 0.014 | -0.022 | -0.031 | -0.012 | -0.013 | -0.013 | -0.019 | -0.0079 | -0.013 | -0.018 | -0.013 | 0.021 | -0.0097 | -0.049 | -0.0016 | 0.0031 | 0.0037 | -0.028 | 0.02 | 0.00096 | -0.0045 | -0.00035 | -0.011 | -0.025 | -0.00099 | -0.0077 | -0.018 | 0.0025 | -0.0089 | -0.01 | 0.00078 | -0.0089 | -0.019 | -0.00084 | -0.0061 | -0.037 | -0.005 | -0.006 | -0.027 | -0.00099 | -0.016 | -0.028 | 0.0027 | -0.0052 | -0.025 | -0.00061 | -0.013 | -0.015 | 0.01 | -0.014 | -0.017 | 0.0063 |
| away_player_Y6 | 0.06 | 0.068 | 0.068 | 0.0096 | -0.028 | -0.0029 | 0.012 | -0.019 | 0.023 | -0.004 | 0.0093 | 0.0092 | 0.0065 | -0.0049 | -0.28 | -0.16 | 0.22 | 0.11 | -0.12 | 0.13 | 0.027 | 0.27 | 0.22 | 0.22 | -0.13 | -0.8 | -0.097 | 0.51 | 0.13 | -0.26 | 0.36 | -0.004 | nan | -0.013 | -0.0089 | 0.0009 | 0.31 | 0.23 | -0.14 | -0.059 | 0.12 | -0.19 | 0.013 | nan | 0.03 | 0.014 | 0.17 | 1 | 0.48 | -0.19 | 0.063 | 0.3 | -0.4 | 0.0028 | 0.014 | 0.015 | 0.0087 | 0.021 | 0.018 | 0.013 | -1.2e-05 | 0.014 | 0.0037 | 0.033 | -0.011 | 0.0099 | -0.0061 | 0.0027 | 0.0097 | 0.04 | -0.017 | -0.012 | 0.024 | -0.024 | 0.037 | 0.057 | -0.0084 | -0.042 | 0.053 | -0.024 | -0.05 | 0.053 | -0.026 | -0.045 | 0.057 | -0.016 | -0.044 | 0.078 | -0.048 | -0.089 | 0.053 | -0.012 | -0.05 | 0.044 | -0.0033 | -0.028 | 0.054 | -0.022 | -0.05 | 0.035 | 0.0029 | -0.023 | 0.038 | 0.0063 | -0.009 |
| away_player_Y7 | -0.017 | -0.0097 | -0.0097 | 0.003 | -0.019 | -0.0084 | 0.0086 | 0.0012 | 0.0019 | -0.0075 | 0.033 | 0.033 | 0.005 | -0.036 | -0.21 | -0.17 | 0.21 | 0.096 | -0.13 | 0.13 | 0.036 | 0.086 | 0.057 | 0.048 | -0.14 | -0.24 | -0.7 | 0.6 | 0.16 | -0.25 | 0.38 | -0.0075 | nan | 0.0035 | 0.0029 | 0.031 | 0.25 | 0.26 | -0.12 | -0.04 | 0.13 | -0.18 | 0.025 | nan | 0.036 | 0.034 | 0.14 | 0.48 | 1 | -0.23 | 0.044 | 0.33 | -0.34 | 0.0062 | 0.016 | 0.018 | 0.0074 | 0.031 | 0.024 | 0.011 | 0.012 | 0.022 | 0.007 | 0.038 | -0.0026 | 0.013 | 0.0094 | -0.0019 | 0.014 | 0.03 | 0.032 | -0.024 | 0.036 | -0.03 | 0.055 | 0.031 | 0.032 | 0.0089 | 0.025 | 0.021 | 0.00055 | 0.025 | 0.015 | 0.0062 | 0.03 | 0.027 | 0.01 | 0.044 | 0.016 | -0.0064 | 0.026 | 0.032 | 0.0046 | 0.018 | 0.016 | 0.0056 | 0.029 | 0.02 | 0.0026 | 0.011 | 0.023 | 0.0097 | 0.014 | 0.026 | 0.023 |
| away_player_Y8 | 0.096 | 0.074 | 0.074 | -0.0096 | 0.21 | 0.011 | 0.0041 | 0.017 | -0.0062 | 0.0084 | -0.052 | -0.024 | -0.045 | 0.095 | 0.2 | 0.15 | -0.28 | -0.11 | 0.21 | -0.16 | 0.033 | -0.039 | -0.019 | -0.027 | 0.095 | 0.38 | 0.4 | -0.75 | -0.12 | 0.53 | -0.48 | 0.0084 | nan | -0.0027 | 0.0088 | -0.098 | -0.14 | -0.12 | 0.32 | 0.048 | -0.2 | 0.22 | 0.027 | nan | 0.031 | 0.036 | -0.099 | -0.19 | -0.23 | 1 | -0.00048 | -0.54 | 0.56 | 0.077 | 0.11 | 0.086 | 0.095 | 0.093 | 0.078 | 0.1 | 0.1 | 0.092 | 0.095 | 0.073 | 0.081 | 0.1 | 0.09 | 0.088 | 0.097 | 0.066 | 0.11 | 0.13 | 0.074 | 0.14 | 0.054 | -0.022 | 0.042 | 0.02 | -0.02 | 0.049 | 0.026 | -0.016 | 0.046 | 0.022 | -0.012 | 0.052 | 0.023 | -0.038 | 0.016 | 0.027 | -0.013 | 0.033 | 0.028 | -0.023 | 0.051 | 0.024 | -0.015 | 0.057 | 0.031 | -0.021 | 0.054 | 0.019 | -0.021 | 0.048 | 0.011 |
| away_player_Y9 | 0.035 | 0.01 | 0.01 | -0.028 | 0.24 | 0.032 | 0.027 | -0.0044 | 0.045 | -0.00013 | 0.012 | 0.02 | -0.0033 | -0.0047 | 0.17 | 0.15 | 0.023 | -0.3 | 0.056 | 0.13 | -0.00018 | 0.028 | 0.086 | 0.021 | 0.028 | 0.26 | 0.34 | 0.29 | -0.9 | 0.029 | 0.56 | -0.00013 | nan | -0.0058 | 0.0023 | -0.002 | -0.057 | -0.046 | 0.044 | 0.31 | 0.015 | 0.009 | -0.00018 | nan | nan | -0.0058 | -0.0026 | 0.063 | 0.044 | -0.00048 | 1 | 0.21 | -0.13 | 0.14 | 0.16 | 0.15 | 0.14 | 0.15 | 0.15 | 0.15 | 0.15 | 0.16 | 0.15 | 0.16 | 0.12 | 0.18 | 0.15 | 0.14 | 0.17 | 0.14 | 0.15 | 0.15 | 0.17 | 0.13 | 0.2 | 0.095 | 0.024 | -0.052 | 0.099 | 0.022 | -0.048 | 0.1 | 0.02 | -0.043 | 0.095 | 0.02 | -0.044 | 0.078 | 0.008 | -0.05 | 0.093 | 0.026 | -0.052 | 0.091 | 0.025 | -0.044 | 0.1 | 0.04 | -0.037 | 0.099 | 0.018 | -0.047 | 0.096 | 0.018 | -0.053 |
| away_player_Y10 | -0.037 | -0.026 | -0.026 | 0.0056 | -0.094 | 0.0041 | 0.016 | -0.014 | 0.048 | 0.011 | 0.02 | 0.0088 | 0.042 | -0.056 | -0.1 | -0.073 | 0.21 | 0.038 | -0.21 | 0.18 | 0.015 | 0.089 | 0.055 | 0.1 | -0.14 | -0.2 | -0.12 | 0.67 | 0.082 | -0.9 | 0.78 | 0.011 | nan | -0.013 | -0.018 | 0.056 | 0.12 | 0.11 | -0.18 | 0.029 | 0.22 | -0.22 | 0.015 | nan | nan | 0.011 | 0.16 | 0.3 | 0.33 | -0.54 | 0.21 | 1 | -0.83 | 0.00057 | -0.011 | -0.0021 | -0.014 | -0.0025 | -0.0077 | -0.02 | -0.0082 | -0.0066 | -0.0086 | 0.024 | -0.01 | -0.018 | -0.02 | -0.012 | -0.011 | 0.0038 | -0.033 | -0.048 | 0.01 | -0.082 | 0.038 | 0.08 | -0.047 | -0.087 | 0.08 | -0.055 | -0.088 | 0.078 | -0.06 | -0.087 | 0.074 | -0.057 | -0.085 | 0.07 | -0.033 | -0.064 | 0.072 | -0.038 | -0.09 | 0.082 | -0.054 | -0.095 | 0.075 | -0.056 | -0.086 | 0.089 | -0.058 | -0.097 | 0.089 | -0.056 | -0.097 |
| away_player_Y11 | 0.0076 | -0.0086 | -0.0086 | -0.0037 | 0.14 | -0.0063 | -0.014 | 0.013 | -0.04 | nan | -0.011 | -0.0027 | -0.028 | 0.035 | 0.2 | 0.13 | -0.25 | -0.072 | 0.22 | -0.21 | nan | -0.024 | 0.023 | -0.04 | 0.067 | 0.36 | 0.18 | -0.62 | -0.13 | 0.79 | -0.81 | nan | nan | 0.007 | 0.01 | -0.032 | -0.2 | -0.17 | 0.22 | 0.00032 | -0.23 | 0.27 | nan | nan | nan | 0.007 | -0.066 | -0.4 | -0.34 | 0.56 | -0.13 | -0.83 | 1 | 0.018 | 0.025 | 0.01 | 0.024 | 0.0085 | 0.016 | 0.028 | 0.021 | 0.014 | 0.022 | -0.017 | 0.028 | 0.027 | 0.015 | 0.029 | 0.023 | -0.00049 | 0.047 | 0.068 | -0.0044 | 0.091 | -0.034 | -0.086 | 0.024 | 0.062 | -0.084 | 0.035 | 0.067 | -0.082 | 0.044 | 0.067 | -0.078 | 0.039 | 0.065 | -0.088 | 0.0097 | 0.054 | -0.076 | 0.014 | 0.069 | -0.083 | 0.031 | 0.067 | -0.08 | 0.037 | 0.066 | -0.085 | 0.036 | 0.071 | -0.086 | 0.031 | 0.067 |
| home_player_1 | 0.11 | 0.073 | 0.073 | -0.0045 | 0.39 | 0.043 | 0.051 | -0.016 | 0.028 | 0.0075 | 0.041 | 0.034 | 0.00051 | -0.024 | 0.094 | 0.099 | -0.026 | -0.13 | 0.053 | 0.0054 | 0.0059 | 0.033 | 0.041 | -0.0004 | -0.021 | 0.09 | 0.089 | -0.013 | -0.13 | 0.029 | 0.033 | 0.006 | 0.0087 | 0.0075 | -0.00016 | 0.021 | -0.00048 | -0.0099 | 0.083 | 0.12 | -0.032 | 0.043 | 0.00073 | nan | 0.0074 | 0.0054 | 0.014 | 0.0028 | 0.0062 | 0.077 | 0.14 | 0.00057 | 0.018 | 1 | 0.3 | 0.25 | 0.27 | 0.27 | 0.26 | 0.27 | 0.27 | 0.26 | 0.29 | 0.27 | 0.17 | 0.23 | 0.2 | 0.21 | 0.22 | 0.22 | 0.23 | 0.24 | 0.25 | 0.23 | 0.23 | 0.056 | -0.024 | -0.074 | 0.061 | -0.026 | -0.074 | 0.063 | -0.026 | -0.073 | 0.069 | -0.013 | -0.061 | 0.065 | -0.07 | -0.1 | 0.058 | -0.029 | -0.072 | 0.032 | -0.023 | -0.062 | 0.065 | -0.0092 | -0.066 | 0.036 | -0.015 | -0.055 | 0.03 | -0.015 | -0.052 |
| home_player_2 | 0.14 | 0.1 | 0.1 | 0.0076 | 0.49 | 0.1 | 0.077 | -0.027 | 0.029 | 0.01 | 0.0099 | 0.024 | -0.016 | 0.01 | 0.11 | 0.11 | -0.032 | -0.17 | 0.071 | 0.025 | -0.0043 | 0.014 | 0.035 | -0.03 | 0.016 | 0.093 | 0.095 | -0.024 | -0.16 | 0.042 | 0.044 | 0.0085 | 0.011 | -0.0055 | -0.01 | -0.015 | 0.0081 | -0.001 | 0.11 | 0.17 | -0.039 | 0.045 | -0.0043 | nan | nan | 0.0086 | -0.022 | 0.014 | 0.016 | 0.11 | 0.16 | -0.011 | 0.025 | 0.3 | 1 | 0.3 | 0.3 | 0.32 | 0.31 | 0.32 | 0.32 | 0.32 | 0.33 | 0.32 | 0.24 | 0.31 | 0.28 | 0.26 | 0.27 | 0.29 | 0.28 | 0.29 | 0.29 | 0.3 | 0.3 | 0.047 | 0.0031 | -0.058 | 0.049 | -0.0058 | -0.057 | 0.052 | -0.0019 | -0.052 | 0.059 | 0.016 | -0.038 | 0.026 | -0.049 | -0.071 | 0.049 | -0.0058 | -0.053 | 0.054 | -0.0085 | -0.068 | 0.053 | 0.02 | -0.044 | 0.06 | -0.0067 | -0.065 | 0.06 | -0.0032 | -0.065 |
| home_player_3 | 0.16 | 0.13 | 0.13 | 0.016 | 0.41 | 0.066 | 0.053 | -0.0039 | 0.028 | 0.0089 | 0.0095 | 0.02 | -0.05 | 0.036 | 0.093 | 0.089 | -0.043 | -0.15 | 0.069 | 0.023 | 0.013 | 0.016 | 0.028 | -0.033 | 0.022 | 0.084 | 0.082 | -0.017 | -0.15 | 0.035 | 0.048 | 0.0081 | 0.0089 | -0.004 | 0.0042 | -0.051 | -0.0013 | -0.0023 | 0.1 | 0.14 | -0.037 | 0.033 | 0.0067 | nan | 0.013 | 0.011 | -0.031 | 0.015 | 0.018 | 0.086 | 0.15 | -0.0021 | 0.01 | 0.25 | 0.3 | 1 | 0.26 | 0.29 | 0.29 | 0.29 | 0.28 | 0.3 | 0.31 | 0.31 | 0.22 | 0.27 | 0.25 | 0.24 | 0.26 | 0.27 | 0.24 | 0.27 | 0.28 | 0.26 | 0.26 | 0.039 | 0.019 | -0.03 | 0.041 | 0.01 | -0.032 | 0.041 | 0.013 | -0.028 | 0.048 | 0.028 | -0.013 | 0.027 | -0.012 | -0.031 | 0.038 | 0.017 | -0.031 | 0.037 | -0.0059 | -0.052 | 0.046 | 0.039 | -0.02 | 0.043 | -0.0084 | -0.049 | 0.039 | -0.00082 | -0.05 |
| home_player_4 | 0.17 | 0.13 | 0.13 | -0.0068 | 0.42 | 0.082 | 0.078 | -0.011 | 0.025 | 0.0092 | 0.044 | 0.053 | -0.026 | -0.0037 | 0.096 | 0.1 | -0.033 | -0.15 | 0.062 | 0.017 | -0.003 | 0.028 | 0.036 | -0.023 | 0.0031 | 0.087 | 0.087 | -0.027 | -0.14 | 0.041 | 0.029 | 0.007 | 0.011 | -0.0036 | -0.0059 | -0.0087 | 0.01 | -0.00067 | 0.099 | 0.14 | -0.035 | 0.041 | -0.0057 | nan | -0.0014 | 0.0015 | -0.012 | 0.0087 | 0.0074 | 0.095 | 0.14 | -0.014 | 0.024 | 0.27 | 0.3 | 0.26 | 1 | 0.3 | 0.29 | 0.27 | 0.29 | 0.31 | 0.32 | 0.31 | 0.21 | 0.25 | 0.23 | 0.24 | 0.23 | 0.26 | 0.24 | 0.27 | 0.27 | 0.27 | 0.26 | 0.051 | 0.008 | -0.043 | 0.052 | 0.0042 | -0.041 | 0.054 | 0.0044 | -0.04 | 0.061 | 0.017 | -0.025 | 0.045 | -0.035 | -0.053 | 0.053 | 0.0045 | -0.042 | 0.048 | -0.014 | -0.057 | 0.058 | 0.025 | -0.03 | 0.042 | -0.019 | -0.051 | 0.04 | -0.018 | -0.054 |
| home_player_5 | 0.11 | 0.073 | 0.073 | 0.0084 | 0.46 | 0.055 | 0.053 | -0.025 | 0.036 | 0.0087 | 0.049 | 0.052 | -0.013 | -0.02 | 0.093 | 0.096 | -0.012 | -0.16 | 0.06 | 0.034 | -0.0063 | 0.019 | 0.041 | -0.02 | 0.0039 | 0.088 | 0.079 | -0.014 | -0.14 | 0.034 | 0.046 | 0.0065 | 0.011 | 0.011 | 0.0081 | 0.006 | 0.018 | 0.016 | 0.087 | 0.15 | -0.026 | 0.032 | -0.0079 | nan | -0.0047 | -0.006 | -0.013 | 0.021 | 0.031 | 0.093 | 0.15 | -0.0025 | 0.0085 | 0.27 | 0.32 | 0.29 | 0.3 | 1 | 0.28 | 0.28 | 0.29 | 0.31 | 0.31 | 0.32 | 0.22 | 0.26 | 0.25 | 0.25 | 0.26 | 0.26 | 0.25 | 0.27 | 0.28 | 0.28 | 0.27 | 0.064 | -0.0037 | -0.066 | 0.065 | -0.012 | -0.066 | 0.068 | -0.0087 | -0.063 | 0.074 | 0.007 | -0.046 | 0.055 | -0.059 | -0.085 | 0.066 | -0.013 | -0.063 | 0.051 | -0.016 | -0.067 | 0.07 | 0.013 | -0.053 | 0.044 | -0.0046 | -0.051 | 0.042 | -0.00015 | -0.052 |
| home_player_6 | 0.15 | 0.11 | 0.11 | 0.013 | 0.47 | 0.079 | 0.058 | -0.01 | 0.037 | 0.009 | 0.015 | 0.036 | -0.022 | -0.00019 | 0.061 | 0.07 | 0.011 | -0.13 | 0.03 | 0.051 | -0.00093 | 0.031 | 0.046 | -0.033 | 0.005 | 0.082 | 0.078 | -0.0025 | -0.15 | 0.037 | 0.045 | 0.007 | 0.011 | 0.0026 | -0.0056 | -0.0089 | 0.041 | 0.04 | 0.064 | 0.14 | -0.0034 | -0.0028 | -0.0022 | nan | -0.00026 | 0.0061 | -0.013 | 0.018 | 0.024 | 0.078 | 0.15 | -0.0077 | 0.016 | 0.26 | 0.31 | 0.29 | 0.29 | 0.28 | 1 | 0.28 | 0.3 | 0.32 | 0.31 | 0.3 | 0.23 | 0.29 | 0.26 | 0.26 | 0.26 | 0.27 | 0.27 | 0.28 | 0.28 | 0.27 | 0.28 | 0.057 | 0.0098 | -0.046 | 0.059 | 0.00095 | -0.045 | 0.062 | 0.0056 | -0.047 | 0.07 | 0.022 | -0.025 | 0.041 | -0.037 | -0.054 | 0.059 | 0.0049 | -0.046 | 0.062 | -0.01 | -0.068 | 0.065 | 0.028 | -0.034 | 0.072 | -0.0018 | -0.058 | 0.071 | 0.0071 | -0.058 |
| home_player_7 | 0.15 | 0.11 | 0.11 | -0.0034 | 0.44 | 0.069 | 0.063 | -0.0065 | 0.018 | 0.0087 | 0.015 | 0.028 | -0.049 | 0.024 | 0.12 | 0.073 | -0.046 | -0.16 | 0.08 | 0.016 | 0.0049 | 0.019 | 0.032 | -0.026 | 0.013 | 0.089 | 0.092 | -0.028 | -0.15 | 0.048 | 0.031 | 0.0072 | 0.0097 | -0.0038 | -0.0089 | -0.035 | -0.0061 | 0.027 | 0.11 | 0.15 | -0.048 | 0.049 | 0.0049 | nan | nan | -0.0031 | -0.019 | 0.013 | 0.011 | 0.1 | 0.15 | -0.02 | 0.028 | 0.27 | 0.32 | 0.29 | 0.27 | 0.28 | 0.28 | 1 | 0.28 | 0.29 | 0.3 | 0.28 | 0.21 | 0.29 | 0.26 | 0.25 | 0.26 | 0.27 | 0.25 | 0.26 | 0.27 | 0.28 | 0.28 | 0.057 | 0.028 | -0.035 | 0.057 | 0.023 | -0.033 | 0.058 | 0.02 | -0.032 | 0.065 | 0.038 | -0.015 | 0.045 | -0.014 | -0.047 | 0.057 | 0.024 | -0.032 | 0.042 | 0.0088 | -0.043 | 0.063 | 0.045 | -0.023 | 0.047 | 0.023 | -0.029 | 0.047 | 0.027 | -0.03 |
| home_player_8 | 0.13 | 0.091 | 0.091 | 0.0096 | 0.48 | 0.07 | 0.065 | -0.017 | 0.022 | 0.012 | 0.054 | 0.053 | -0.0032 | -0.028 | 0.13 | 0.14 | -0.068 | -0.16 | 0.098 | -0.019 | 0.0095 | 0.021 | 0.038 | -0.016 | -0.00019 | 0.11 | 0.086 | -0.024 | -0.15 | 0.039 | 0.034 | 0.011 | 0.011 | 0.0075 | 0.002 | 0.024 | -0.0061 | -0.026 | 0.14 | 0.15 | -0.067 | 0.076 | 0.0061 | nan | 0.0097 | 0.0067 | -0.0079 | -1.2e-05 | 0.012 | 0.1 | 0.15 | -0.0082 | 0.021 | 0.27 | 0.32 | 0.28 | 0.29 | 0.29 | 0.3 | 0.28 | 1 | 0.31 | 0.32 | 0.31 | 0.23 | 0.29 | 0.26 | 0.25 | 0.26 | 0.28 | 0.26 | 0.28 | 0.29 | 0.28 | 0.27 | 0.05 | 0.0091 | -0.044 | 0.053 | 0.0047 | -0.043 | 0.052 | 0.01 | -0.043 | 0.06 | 0.022 | -0.023 | 0.04 | -0.029 | -0.045 | 0.053 | 0.0047 | -0.041 | 0.041 | -0.0037 | -0.058 | 0.057 | 0.028 | -0.029 | 0.061 | -0.011 | -0.065 | 0.057 | -0.0091 | -0.063 |
| home_player_9 | 0.12 | 0.076 | 0.076 | -2.1e-05 | 0.49 | 0.095 | 0.058 | -0.013 | 0.025 | 0.0086 | 0.029 | 0.04 | -0.027 | -0.0014 | 0.082 | 0.08 | 0.0051 | -0.16 | 0.048 | 0.049 | -0.0064 | 0.033 | 0.028 | -0.017 | 0.0008 | 0.093 | 0.081 | -0.012 | -0.15 | 0.036 | 0.047 | 0.0064 | 0.01 | 0.0042 | 0.002 | -0.0075 | 0.031 | 0.033 | 0.078 | 0.16 | -0.015 | 0.016 | -0.0077 | nan | -0.005 | -0.00075 | -0.013 | 0.014 | 0.022 | 0.092 | 0.16 | -0.0066 | 0.014 | 0.26 | 0.32 | 0.3 | 0.31 | 0.31 | 0.32 | 0.29 | 0.31 | 1 | 0.32 | 0.3 | 0.23 | 0.31 | 0.27 | 0.27 | 0.28 | 0.29 | 0.29 | 0.29 | 0.3 | 0.29 | 0.29 | 0.035 | 0.011 | -0.038 | 0.036 | 0.0053 | -0.037 | 0.04 | 0.011 | -0.036 | 0.046 | 0.027 | -0.018 | 0.019 | -0.043 | -0.054 | 0.036 | 0.0061 | -0.034 | 0.031 | 0.0028 | -0.041 | 0.042 | 0.031 | -0.026 | 0.03 | 0.025 | -0.019 | 0.033 | 0.028 | -0.025 |
| home_player_10 | 0.14 | 0.1 | 0.1 | 0.015 | 0.47 | 0.077 | 0.07 | -0.034 | 0.026 | 0.0048 | 0.034 | 0.044 | -0.026 | -0.0051 | 0.13 | 0.13 | -0.081 | -0.16 | 0.12 | -0.043 | -0.0052 | 0.022 | 0.037 | -0.031 | 0.0085 | 0.097 | 0.096 | -0.027 | -0.15 | 0.037 | 0.036 | 0.0037 | 0.0058 | -0.0051 | -0.00026 | -0.0034 | -0.024 | -0.036 | 0.14 | 0.13 | -0.096 | 0.1 | -0.0052 | nan | -0.0044 | -0.0043 | -0.018 | 0.0037 | 0.007 | 0.095 | 0.15 | -0.0086 | 0.022 | 0.29 | 0.33 | 0.31 | 0.32 | 0.31 | 0.31 | 0.3 | 0.32 | 0.32 | 1 | 0.32 | 0.24 | 0.3 | 0.26 | 0.27 | 0.27 | 0.28 | 0.27 | 0.29 | 0.29 | 0.28 | 0.28 | 0.076 | -0.025 | -0.09 | 0.078 | -0.032 | -0.088 | 0.081 | -0.031 | -0.088 | 0.088 | -0.015 | -0.069 | 0.071 | -0.073 | -0.1 | 0.08 | -0.035 | -0.085 | 0.071 | -0.043 | -0.098 | 0.084 | -0.0081 | -0.077 | 0.063 | -0.048 | -0.096 | 0.063 | -0.047 | -0.097 |
| home_player_11 | 0.11 | 0.074 | 0.074 | -0.0039 | 0.44 | 0.076 | 0.054 | -0.034 | 0.031 | 0.01 | 0.019 | 0.022 | -0.024 | 0.0082 | 0.085 | 0.066 | 0.029 | -0.19 | 0.035 | 0.097 | 0.0036 | 0.025 | 0.032 | -0.033 | 0.0053 | 0.078 | 0.072 | 0.01 | -0.15 | 0.011 | 0.073 | 0.01 | 0.0092 | -0.004 | 5.3e-05 | -0.014 | 0.044 | 0.053 | 0.058 | 0.2 | 0.017 | -0.021 | 0.0025 | nan | 0.0036 | 0.0033 | -0.013 | 0.033 | 0.038 | 0.073 | 0.16 | 0.024 | -0.017 | 0.27 | 0.32 | 0.31 | 0.31 | 0.32 | 0.3 | 0.28 | 0.31 | 0.3 | 0.32 | 1 | 0.23 | 0.3 | 0.26 | 0.27 | 0.26 | 0.28 | 0.27 | 0.28 | 0.28 | 0.28 | 0.28 | 0.072 | -0.012 | -0.075 | 0.074 | -0.023 | -0.075 | 0.075 | -0.024 | -0.075 | 0.082 | -0.0053 | -0.058 | 0.07 | -0.065 | -0.095 | 0.071 | -0.015 | -0.075 | 0.054 | -0.026 | -0.078 | 0.08 | 0.0046 | -0.061 | 0.056 | -0.033 | -0.078 | 0.054 | -0.028 | -0.078 |
| away_player_1 | 0.1 | 0.07 | 0.07 | 0.0026 | 0.39 | 0.048 | 0.047 | 0.035 | -0.013 | 0.0099 | 0.036 | 0.042 | -0.01 | -0.019 | 0.092 | 0.096 | -0.022 | -0.14 | 0.055 | 0.024 | 0.0088 | 0.039 | 0.043 | -0.0099 | -0.026 | 0.1 | 0.092 | -0.021 | -0.13 | 0.028 | 0.022 | 0.011 | 0.0078 | -0.0036 | -0.001 | 0.012 | 0.0076 | 0.0078 | 0.085 | 0.14 | -0.021 | 0.024 | 0.012 | nan | 0.0064 | 0.0087 | 0.021 | -0.011 | -0.0026 | 0.081 | 0.12 | -0.01 | 0.028 | 0.17 | 0.24 | 0.22 | 0.21 | 0.22 | 0.23 | 0.21 | 0.23 | 0.23 | 0.24 | 0.23 | 1 | 0.3 | 0.25 | 0.27 | 0.27 | 0.26 | 0.28 | 0.27 | 0.26 | 0.27 | 0.26 | -0.068 | 0.047 | 0.051 | -0.066 | 0.046 | 0.056 | -0.065 | 0.048 | 0.054 | -0.06 | 0.06 | 0.072 | -0.11 | 0.022 | 0.067 | -0.066 | 0.042 | 0.052 | -0.054 | 0.034 | 0.027 | -0.062 | 0.065 | 0.064 | -0.056 | 0.034 | 0.036 | -0.052 | 0.036 | 0.03 |
| away_player_2 | 0.15 | 0.1 | 0.1 | 0.012 | 0.49 | 0.062 | 0.095 | 0.028 | -0.0067 | 0.0075 | 0.03 | 0.043 | -0.031 | 0.0098 | 0.097 | 0.097 | -0.031 | -0.17 | 0.076 | 0.023 | 0.0015 | 0.021 | 0.026 | -0.035 | 0.0091 | 0.11 | 0.1 | -0.023 | -0.17 | 0.054 | 0.04 | 0.0057 | 0.0091 | -0.0046 | 0.00018 | -0.018 | 0.021 | 0.011 | 0.11 | 0.16 | -0.039 | 0.043 | -0.0028 | nan | 0.0032 | 0.0011 | -0.0097 | 0.0099 | 0.013 | 0.1 | 0.18 | -0.018 | 0.027 | 0.23 | 0.31 | 0.27 | 0.25 | 0.26 | 0.29 | 0.29 | 0.29 | 0.31 | 0.3 | 0.3 | 0.3 | 1 | 0.3 | 0.31 | 0.33 | 0.31 | 0.32 | 0.32 | 0.32 | 0.34 | 0.34 | -0.033 | 0.062 | 0.037 | -0.032 | 0.053 | 0.039 | -0.028 | 0.06 | 0.041 | -0.023 | 0.076 | 0.062 | -0.057 | 0.019 | 0.037 | -0.031 | 0.054 | 0.04 | -0.037 | 0.042 | 0.023 | -0.025 | 0.081 | 0.051 | -0.05 | 0.057 | 0.05 | -0.051 | 0.061 | 0.042 |
| away_player_3 | 0.16 | 0.13 | 0.13 | 0.012 | 0.41 | 0.049 | 0.072 | 0.027 | -0.007 | 0.009 | 0.029 | 0.028 | -0.021 | 0.0088 | 0.094 | 0.083 | -0.021 | -0.16 | 0.059 | 0.036 | 0.0044 | 1.6e-05 | 0.0089 | -0.047 | 0.035 | 0.097 | 0.079 | -0.028 | -0.16 | 0.049 | 0.041 | 0.0072 | 0.01 | -0.004 | -0.0089 | -0.019 | 0.019 | 0.025 | 0.089 | 0.16 | -0.021 | 0.028 | -0.00056 | nan | 0.006 | 0.0039 | -0.049 | -0.0061 | 0.0094 | 0.09 | 0.15 | -0.02 | 0.015 | 0.2 | 0.28 | 0.25 | 0.23 | 0.25 | 0.26 | 0.26 | 0.26 | 0.27 | 0.26 | 0.26 | 0.25 | 0.3 | 1 | 0.26 | 0.29 | 0.3 | 0.28 | 0.28 | 0.3 | 0.3 | 0.31 | -0.02 | 0.054 | 0.031 | -0.019 | 0.049 | 0.034 | -0.016 | 0.047 | 0.033 | -0.012 | 0.062 | 0.049 | -0.028 | 0.014 | 0.016 | -0.019 | 0.052 | 0.031 | -0.044 | 0.051 | 0.043 | -0.015 | 0.074 | 0.041 | -0.053 | 0.068 | 0.068 | -0.054 | 0.073 | 0.059 |
| away_player_4 | 0.16 | 0.13 | 0.13 | 0.0017 | 0.43 | 0.069 | 0.083 | 0.017 | -0.0065 | 0.0085 | 0.025 | 0.023 | -0.015 | 0.0063 | 0.079 | 0.08 | -0.022 | -0.13 | 0.053 | 0.029 | 0.0027 | 0.034 | 0.049 | -0.021 | -0.006 | 0.093 | 0.097 | -0.025 | -0.14 | 0.036 | 0.023 | 0.0066 | 0.01 | -2.9e-05 | 9.4e-05 | -0.016 | 0.019 | 0.013 | 0.084 | 0.13 | -0.021 | 0.017 | -0.0017 | nan | 0.0042 | 0.0062 | -0.0016 | 0.0027 | -0.0019 | 0.088 | 0.14 | -0.012 | 0.029 | 0.21 | 0.26 | 0.24 | 0.24 | 0.25 | 0.26 | 0.25 | 0.25 | 0.27 | 0.27 | 0.27 | 0.27 | 0.31 | 0.26 | 1 | 0.29 | 0.28 | 0.28 | 0.3 | 0.31 | 0.32 | 0.31 | -0.017 | 0.057 | 0.024 | -0.017 | 0.051 | 0.031 | -0.015 | 0.048 | 0.028 | -0.0072 | 0.066 | 0.044 | -0.034 | 0.022 | 0.019 | -0.014 | 0.049 | 0.031 | -0.036 | 0.039 | 0.029 | -0.0095 | 0.075 | 0.04 | -0.038 | 0.047 | 0.044 | -0.038 | 0.047 | 0.035 |
| away_player_5 | 0.11 | 0.068 | 0.068 | 0.011 | 0.46 | 0.058 | 0.059 | 0.023 | -0.011 | 0.012 | 0.03 | 0.04 | -0.022 | -0.0031 | 0.089 | 0.084 | -0.022 | -0.14 | 0.058 | 0.028 | 0.0017 | 0.038 | 0.047 | -0.0057 | -0.012 | 0.1 | 0.089 | -0.017 | -0.16 | 0.05 | 0.041 | 0.0098 | 0.013 | -0.0037 | 0.0036 | -0.0084 | 0.022 | 0.024 | 0.097 | 0.15 | -0.021 | 0.024 | -0.0021 | nan | 0.003 | 0.0076 | 0.0031 | 0.0097 | 0.014 | 0.097 | 0.17 | -0.011 | 0.023 | 0.22 | 0.27 | 0.26 | 0.23 | 0.26 | 0.26 | 0.26 | 0.26 | 0.28 | 0.27 | 0.26 | 0.27 | 0.33 | 0.29 | 0.29 | 1 | 0.28 | 0.28 | 0.29 | 0.31 | 0.32 | 0.32 | -0.037 | 0.049 | 0.031 | -0.037 | 0.041 | 0.034 | -0.036 | 0.043 | 0.037 | -0.029 | 0.058 | 0.051 | -0.062 | -0.0081 | 0.022 | -0.034 | 0.041 | 0.037 | -0.041 | 0.041 | 0.027 | -0.03 | 0.066 | 0.045 | -0.031 | 0.059 | 0.042 | -0.031 | 0.062 | 0.036 |
| away_player_6 | 0.14 | 0.11 | 0.11 | 0.013 | 0.47 | 0.055 | 0.067 | 0.016 | 0.0064 | 0.011 | 0.028 | 0.039 | -0.016 | -0.004 | 0.082 | 0.088 | -0.021 | -0.14 | 0.06 | 0.029 | -0.0032 | 0.03 | 0.038 | -0.017 | -0.012 | 0.063 | 0.076 | 0.0077 | -0.13 | 0.024 | 0.05 | 0.0088 | 0.013 | -0.0038 | -0.0053 | -0.0048 | 0.023 | 0.021 | 0.094 | 0.14 | -0.027 | 0.029 | -0.0019 | nan | -0.0033 | -0.00019 | 0.0037 | 0.04 | 0.03 | 0.066 | 0.14 | 0.0038 | -0.00049 | 0.22 | 0.29 | 0.27 | 0.26 | 0.26 | 0.27 | 0.27 | 0.28 | 0.29 | 0.28 | 0.28 | 0.26 | 0.31 | 0.3 | 0.28 | 0.28 | 1 | 0.29 | 0.3 | 0.31 | 0.31 | 0.3 | -0.018 | 0.046 | 0.021 | -0.017 | 0.037 | 0.025 | -0.018 | 0.043 | 0.025 | -0.0054 | 0.059 | 0.041 | -0.035 | -0.0018 | 0.012 | -0.017 | 0.042 | 0.025 | -0.045 | 0.037 | 0.027 | -0.011 | 0.065 | 0.034 | -0.061 | 0.061 | 0.064 | -0.057 | 0.068 | 0.059 |
| away_player_7 | 0.14 | 0.11 | 0.11 | 0.0064 | 0.44 | 0.054 | 0.078 | 0.025 | 0.0047 | 0.0084 | 0.024 | 0.039 | -0.028 | 0.0087 | 0.089 | 0.091 | -0.029 | -0.15 | 0.068 | 0.026 | -0.00099 | 0.0033 | 0.023 | -0.037 | 0.021 | 0.13 | 0.068 | -0.04 | -0.16 | 0.069 | 0.017 | 0.0066 | 0.0098 | -0.0036 | -0.0021 | -0.017 | 0.014 | 0.013 | 0.098 | 0.15 | -0.034 | 0.036 | -0.002 | nan | -0.00042 | 0.0011 | -0.028 | -0.017 | 0.032 | 0.11 | 0.15 | -0.033 | 0.047 | 0.23 | 0.28 | 0.24 | 0.24 | 0.25 | 0.27 | 0.25 | 0.26 | 0.29 | 0.27 | 0.27 | 0.28 | 0.32 | 0.28 | 0.28 | 0.28 | 0.29 | 1 | 0.29 | 0.28 | 0.31 | 0.29 | -0.017 | 0.066 | 0.035 | -0.016 | 0.059 | 0.038 | -0.014 | 0.061 | 0.039 | -0.0076 | 0.076 | 0.058 | -0.037 | 0.029 | 0.037 | -0.016 | 0.06 | 0.037 | -0.027 | 0.046 | 0.025 | -0.0096 | 0.082 | 0.046 | -0.027 | 0.052 | 0.034 | -0.024 | 0.058 | 0.031 |
| away_player_8 | 0.12 | 0.085 | 0.085 | 0.017 | 0.48 | 0.045 | 0.067 | 0.011 | -0.00041 | 0.011 | 0.028 | 0.03 | -0.021 | 0.0033 | 0.1 | 0.092 | -0.038 | -0.15 | 0.066 | 0.023 | 0.0012 | 0.043 | 0.053 | -0.004 | -0.026 | 0.12 | 0.13 | -0.059 | -0.16 | 0.076 | -0.0057 | 0.011 | 0.0099 | -0.0049 | -0.0024 | -0.012 | 0.0054 | 0.0069 | 0.11 | 0.15 | -0.033 | 0.032 | 0.0051 | nan | -0.00063 | -0.0024 | 0.02 | -0.012 | -0.024 | 0.13 | 0.15 | -0.048 | 0.068 | 0.24 | 0.29 | 0.27 | 0.27 | 0.27 | 0.28 | 0.26 | 0.28 | 0.29 | 0.29 | 0.28 | 0.27 | 0.32 | 0.28 | 0.3 | 0.29 | 0.3 | 0.29 | 1 | 0.32 | 0.32 | 0.32 | -0.029 | 0.056 | 0.035 | -0.028 | 0.051 | 0.039 | -0.029 | 0.056 | 0.039 | -0.017 | 0.069 | 0.056 | -0.045 | 0.016 | 0.033 | -0.027 | 0.051 | 0.037 | -0.051 | 0.045 | 0.031 | -0.021 | 0.074 | 0.048 | -0.05 | 0.045 | 0.039 | -0.047 | 0.046 | 0.032 |
| away_player_9 | 0.12 | 0.076 | 0.076 | 0.0048 | 0.49 | 0.052 | 0.087 | 0.013 | -0.0039 | 0.015 | 0.025 | 0.047 | -0.032 | 0.0063 | 0.094 | 0.095 | -0.024 | -0.16 | 0.06 | 0.039 | 0.0044 | 0.035 | 0.041 | -0.017 | -0.012 | 0.094 | 0.083 | 0.011 | -0.16 | 0.019 | 0.067 | 0.015 | 0.013 | -0.0041 | -0.00033 | -0.02 | 0.012 | 0.0091 | 0.094 | 0.16 | -0.023 | 0.022 | 0.0048 | nan | 0.0036 | 0.005 | 0.00096 | 0.024 | 0.036 | 0.074 | 0.17 | 0.01 | -0.0044 | 0.25 | 0.29 | 0.28 | 0.27 | 0.28 | 0.28 | 0.27 | 0.29 | 0.3 | 0.29 | 0.28 | 0.26 | 0.32 | 0.3 | 0.31 | 0.31 | 0.31 | 0.28 | 0.32 | 1 | 0.33 | 0.32 | -0.033 | 0.054 | 0.03 | -0.031 | 0.046 | 0.032 | -0.029 | 0.054 | 0.034 | -0.023 | 0.068 | 0.054 | -0.065 | 0.0029 | 0.029 | -0.031 | 0.048 | 0.034 | -0.026 | 0.055 | 0.026 | -0.026 | 0.074 | 0.045 | -0.015 | 0.054 | 0.027 | -0.016 | 0.059 | 0.024 |
| away_player_10 | 0.14 | 0.1 | 0.1 | 0.011 | 0.47 | 0.063 | 0.083 | 0.026 | -0.022 | 0.013 | 0.036 | 0.031 | -0.041 | 0.014 | 0.093 | 0.094 | -0.033 | -0.16 | 0.065 | 0.03 | -0.00076 | 0.028 | 0.035 | -0.028 | -0.0017 | 0.13 | 0.12 | -0.082 | -0.15 | 0.1 | -0.038 | 0.012 | 0.012 | -0.0046 | -0.00036 | -0.025 | 0.017 | 0.015 | 0.099 | 0.15 | -0.032 | 0.032 | -0.00076 | nan | nan | 0.0035 | -0.0045 | -0.024 | -0.03 | 0.14 | 0.13 | -0.082 | 0.091 | 0.23 | 0.3 | 0.26 | 0.27 | 0.28 | 0.27 | 0.28 | 0.28 | 0.29 | 0.28 | 0.28 | 0.27 | 0.34 | 0.3 | 0.32 | 0.32 | 0.31 | 0.31 | 0.32 | 0.33 | 1 | 0.31 | -0.071 | 0.054 | 0.053 | -0.07 | 0.047 | 0.057 | -0.069 | 0.049 | 0.056 | -0.062 | 0.066 | 0.076 | -0.1 | 0.018 | 0.058 | -0.069 | 0.048 | 0.057 | -0.08 | 0.046 | 0.052 | -0.065 | 0.077 | 0.069 | -0.09 | 0.056 | 0.069 | -0.088 | 0.06 | 0.064 |
| away_player_11 | 0.11 | 0.077 | 0.077 | 0.0049 | 0.45 | 0.06 | 0.09 | 0.024 | -0.0074 | 0.0077 | 0.03 | 0.035 | -0.023 | -0.0068 | 0.081 | 0.074 | 0.014 | -0.16 | 0.034 | 0.067 | 0.0098 | 0.019 | 0.024 | -0.015 | -0.0052 | 0.087 | 0.073 | 0.04 | -0.18 | 0.01 | 0.11 | 0.0058 | 0.0092 | -0.00058 | -0.00092 | -0.0043 | 0.033 | 0.037 | 0.066 | 0.16 | 0.0039 | -0.0036 | 0.0021 | nan | 0.012 | 0.0085 | -0.00035 | 0.037 | 0.055 | 0.054 | 0.2 | 0.038 | -0.034 | 0.23 | 0.3 | 0.26 | 0.26 | 0.27 | 0.28 | 0.28 | 0.27 | 0.29 | 0.28 | 0.28 | 0.26 | 0.34 | 0.31 | 0.31 | 0.32 | 0.3 | 0.29 | 0.32 | 0.32 | 0.31 | 1 | -0.058 | 0.047 | 0.041 | -0.057 | 0.04 | 0.046 | -0.056 | 0.043 | 0.045 | -0.05 | 0.055 | 0.061 | -0.083 | 0.00098 | 0.038 | -0.057 | 0.044 | 0.041 | -0.065 | 0.04 | 0.041 | -0.051 | 0.064 | 0.053 | -0.068 | 0.056 | 0.066 | -0.067 | 0.06 | 0.055 |
| B365H | 0.064 | 0.06 | 0.06 | 0.0072 | 0.046 | 0.045 | -0.032 | -0.26 | 0.3 | -0.0039 | -0.021 | -0.012 | -0.016 | 0.00076 | 0.018 | -0.03 | -0.027 | 0.027 | 0.04 | -0.051 | -0.0021 | 0.026 | 0.013 | 0.001 | 0.012 | -0.021 | 0.028 | 0.061 | -0.074 | -0.056 | 0.11 | -0.0043 | -0.003 | -0.0022 | -0.0072 | -0.01 | -0.018 | 0.016 | 0.017 | -0.039 | -0.056 | 0.039 | -0.0041 | nan | -0.00095 | -0.00023 | -0.011 | 0.057 | 0.031 | -0.022 | 0.095 | 0.08 | -0.086 | 0.056 | 0.047 | 0.039 | 0.051 | 0.064 | 0.057 | 0.057 | 0.05 | 0.035 | 0.076 | 0.072 | -0.068 | -0.033 | -0.02 | -0.017 | -0.037 | -0.018 | -0.017 | -0.029 | -0.033 | -0.071 | -0.058 | 1 | 0.018 | -0.47 | 0.99 | 0.021 | -0.48 | 0.98 | 0.0053 | -0.5 | 0.99 | 0.015 | -0.47 | 0.99 | 0.033 | -0.43 | 0.99 | 0.012 | -0.46 | 0.99 | -0.022 | -0.49 | 0.99 | 0.017 | -0.44 | 0.99 | -0.026 | -0.52 | 0.99 | -0.033 | -0.51 |
| B365D | 0.1 | 0.093 | 0.093 | 0.031 | 0.11 | -0.022 | 0.018 | 0.27 | -0.074 | 0.0057 | 0.0046 | -0.009 | -0.028 | 0.028 | 0.013 | 0.029 | 0.035 | -0.1 | -0.0032 | 0.091 | -0.0046 | -0.02 | -0.024 | -0.044 | 0.018 | 0.039 | -0.011 | -0.02 | -0.034 | 0.051 | -0.0086 | 0.0045 | 0.0065 | -0.0027 | -0.00058 | -0.024 | 0.047 | 0.042 | 0.025 | 0.12 | 0.035 | -0.047 | -0.0049 | nan | -0.0038 | -0.0057 | -0.025 | -0.0084 | 0.032 | 0.042 | 0.024 | -0.047 | 0.024 | -0.024 | 0.0031 | 0.019 | 0.008 | -0.0037 | 0.0098 | 0.028 | 0.0091 | 0.011 | -0.025 | -0.012 | 0.047 | 0.062 | 0.054 | 0.057 | 0.049 | 0.046 | 0.066 | 0.056 | 0.054 | 0.054 | 0.047 | 0.018 | 1 | 0.82 | 0.0016 | 0.97 | 0.81 | -0.012 | 0.96 | 0.81 | 0.012 | 0.97 | 0.82 | 0.072 | 0.98 | 0.83 | 0.014 | 0.96 | 0.83 | -0.016 | 0.97 | 0.83 | 0.039 | 0.98 | 0.84 | -0.038 | 0.98 | 0.82 | -0.033 | 0.98 | 0.83 |
| B365A | 0.036 | 0.034 | 0.034 | 0.0098 | 0.0084 | -0.036 | 0.039 | 0.36 | -0.23 | 0.0057 | 0.019 | 0.002 | -0.0065 | 0.011 | -0.0066 | 0.024 | 0.057 | -0.084 | -0.035 | 0.1 | -0.003 | -0.026 | -0.025 | -0.03 | -0.0066 | 0.032 | -0.043 | -0.037 | 0.03 | 0.072 | -0.073 | 0.0053 | 0.0058 | -0.0019 | 0.0042 | -0.0034 | 0.039 | 0.024 | -0.017 | 0.1 | 0.064 | -0.07 | -0.0021 | nan | -0.003 | -0.0044 | -0.00099 | -0.042 | 0.0089 | 0.02 | -0.052 | -0.087 | 0.062 | -0.074 | -0.058 | -0.03 | -0.043 | -0.066 | -0.046 | -0.035 | -0.044 | -0.038 | -0.09 | -0.075 | 0.051 | 0.037 | 0.031 | 0.024 | 0.031 | 0.021 | 0.035 | 0.035 | 0.03 | 0.053 | 0.041 | -0.47 | 0.82 | 1 | -0.49 | 0.82 | 0.97 | -0.5 | 0.82 | 0.97 | -0.48 | 0.81 | 0.97 | -0.43 | 0.83 | 0.98 | -0.48 | 0.81 | 0.97 | -0.49 | 0.82 | 0.98 | -0.45 | 0.81 | 0.97 | -0.52 | 0.82 | 0.98 | -0.51 | 0.83 | 0.98 |
| BWH | 0.061 | 0.057 | 0.057 | 0.007 | 0.051 | 0.046 | -0.033 | -0.26 | 0.3 | -0.0031 | -0.02 | -0.012 | -0.017 | -0.0027 | 0.027 | -0.027 | -0.032 | 0.024 | 0.046 | -0.054 | -0.0018 | 0.026 | 0.014 | 0.0046 | 0.0096 | -0.016 | 0.034 | 0.058 | -0.078 | -0.055 | 0.11 | -0.0037 | -0.0022 | -0.0017 | -0.0071 | -0.0073 | -0.025 | 0.012 | 0.022 | -0.038 | -0.06 | 0.044 | -0.004 | nan | -0.00067 | -7.3e-05 | -0.0077 | 0.053 | 0.025 | -0.02 | 0.099 | 0.08 | -0.084 | 0.061 | 0.049 | 0.041 | 0.052 | 0.065 | 0.059 | 0.057 | 0.053 | 0.036 | 0.078 | 0.074 | -0.066 | -0.032 | -0.019 | -0.017 | -0.037 | -0.017 | -0.016 | -0.028 | -0.031 | -0.07 | -0.057 | 0.99 | 0.0016 | -0.49 | 1 | 0.0033 | -0.5 | 0.98 | -0.011 | -0.52 | 0.98 | -0.00041 | -0.48 | 0.98 | 0.018 | -0.45 | 0.98 | -0.0042 | -0.48 | 0.99 | -0.035 | -0.5 | 0.98 | 0.0013 | -0.45 | 0.99 | -0.039 | -0.54 | 0.99 | -0.048 | -0.52 |
| BWD | 0.11 | 0.096 | 0.096 | 0.04 | 0.099 | -0.02 | 0.018 | 0.27 | -0.072 | 0.0046 | 0.0078 | -0.0092 | -0.024 | 0.021 | 0.025 | 0.035 | 0.026 | -0.1 | 0.0029 | 0.082 | -0.0047 | -0.018 | -0.024 | -0.043 | 0.011 | 0.053 | -0.0056 | -0.03 | -0.034 | 0.057 | -0.018 | 0.0038 | 0.0052 | -0.0023 | 0.00042 | -0.016 | 0.033 | 0.03 | 0.028 | 0.11 | 0.027 | -0.038 | -0.0043 | nan | -0.0042 | -0.0057 | -0.018 | -0.024 | 0.021 | 0.049 | 0.022 | -0.055 | 0.035 | -0.026 | -0.0058 | 0.01 | 0.0042 | -0.012 | 0.00095 | 0.023 | 0.0047 | 0.0053 | -0.032 | -0.023 | 0.046 | 0.053 | 0.049 | 0.051 | 0.041 | 0.037 | 0.059 | 0.051 | 0.046 | 0.047 | 0.04 | 0.021 | 0.97 | 0.82 | 0.0033 | 1 | 0.81 | -0.01 | 0.96 | 0.8 | 0.014 | 0.96 | 0.82 | 0.073 | 0.97 | 0.83 | 0.016 | 0.96 | 0.82 | -0.01 | 0.97 | 0.82 | 0.04 | 0.97 | 0.84 | -0.032 | 0.98 | 0.81 | -0.027 | 0.97 | 0.82 |
| BWA | 0.041 | 0.038 | 0.038 | 0.012 | 0.014 | -0.036 | 0.041 | 0.35 | -0.23 | 0.0065 | 0.025 | 0.0063 | -0.0018 | 0.0027 | -0.00053 | 0.033 | 0.055 | -0.087 | -0.034 | 0.1 | -0.0029 | -0.021 | -0.022 | -0.031 | -0.0098 | 0.041 | -0.033 | -0.042 | 0.025 | 0.073 | -0.076 | 0.0061 | 0.0064 | -0.0018 | 0.006 | 0.0056 | 0.035 | 0.016 | -0.015 | 0.1 | 0.063 | -0.066 | -0.0018 | nan | -0.003 | -0.0043 | 0.0025 | -0.05 | 0.00055 | 0.026 | -0.048 | -0.088 | 0.067 | -0.074 | -0.057 | -0.032 | -0.041 | -0.066 | -0.045 | -0.033 | -0.043 | -0.037 | -0.088 | -0.075 | 0.056 | 0.039 | 0.034 | 0.031 | 0.034 | 0.025 | 0.038 | 0.039 | 0.032 | 0.057 | 0.046 | -0.48 | 0.81 | 0.97 | -0.5 | 0.81 | 1 | -0.51 | 0.81 | 0.97 | -0.49 | 0.8 | 0.96 | -0.44 | 0.81 | 0.98 | -0.49 | 0.8 | 0.97 | -0.51 | 0.8 | 0.97 | -0.47 | 0.8 | 0.97 | -0.54 | 0.81 | 0.98 | -0.53 | 0.81 | 0.97 |
| IWH | 0.063 | 0.058 | 0.058 | 0.012 | 0.057 | 0.041 | -0.033 | -0.27 | 0.3 | -0.0031 | -0.019 | -0.0097 | -0.013 | -0.0025 | 0.024 | -0.025 | -0.031 | 0.023 | 0.046 | -0.054 | -0.0022 | 0.028 | 0.014 | 0.0052 | 0.011 | -0.016 | 0.037 | 0.057 | -0.081 | -0.053 | 0.11 | -0.0036 | -0.0023 | -0.0022 | -0.0076 | -0.0076 | -0.02 | 0.014 | 0.022 | -0.036 | -0.06 | 0.045 | -0.0038 | nan | -0.0013 | -0.00045 | -0.0089 | 0.053 | 0.025 | -0.016 | 0.1 | 0.078 | -0.082 | 0.063 | 0.052 | 0.041 | 0.054 | 0.068 | 0.062 | 0.058 | 0.052 | 0.04 | 0.081 | 0.075 | -0.065 | -0.028 | -0.016 | -0.015 | -0.036 | -0.018 | -0.014 | -0.029 | -0.029 | -0.069 | -0.056 | 0.98 | -0.012 | -0.5 | 0.98 | -0.01 | -0.51 | 1 | -0.024 | -0.53 | 0.98 | -0.013 | -0.5 | 0.97 | 0.0047 | -0.46 | 0.98 | -0.018 | -0.49 | 0.98 | -0.049 | -0.51 | 0.97 | -0.013 | -0.46 | 0.99 | -0.057 | -0.55 | 0.98 | -0.065 | -0.54 |
| IWD | 0.096 | 0.082 | 0.082 | 0.05 | 0.12 | -0.018 | 0.023 | 0.27 | -0.083 | 0.0054 | 0.013 | -0.0012 | -0.02 | 0.013 | 0.029 | 0.044 | 0.023 | -0.1 | 0.0047 | 0.074 | -0.005 | -0.014 | -0.019 | -0.036 | 0.0026 | 0.055 | -0.001 | -0.03 | -0.034 | 0.06 | -0.025 | 0.0043 | 0.0061 | -0.0026 | 0.0011 | -0.0074 | 0.027 | 0.018 | 0.028 | 0.11 | 0.024 | -0.03 | -0.005 | nan | -0.0043 | -0.0057 | -0.01 | -0.026 | 0.015 | 0.046 | 0.02 | -0.06 | 0.044 | -0.026 | -0.0019 | 0.013 | 0.0044 | -0.0087 | 0.0056 | 0.02 | 0.01 | 0.011 | -0.031 | -0.024 | 0.048 | 0.06 | 0.047 | 0.048 | 0.043 | 0.043 | 0.061 | 0.056 | 0.054 | 0.049 | 0.043 | 0.0053 | 0.96 | 0.82 | -0.011 | 0.96 | 0.81 | -0.024 | 1 | 0.83 | -0.00081 | 0.95 | 0.82 | 0.066 | 0.95 | 0.83 | 0.0022 | 0.95 | 0.83 | -0.029 | 0.96 | 0.82 | 0.026 | 0.95 | 0.84 | -0.059 | 0.96 | 0.82 | -0.055 | 0.96 | 0.83 |
| IWA | 0.041 | 0.039 | 0.039 | 0.018 | 0.012 | -0.038 | 0.036 | 0.36 | -0.23 | 0.0071 | 0.02 | 0.0022 | -0.0064 | 0.01 | -2.4e-05 | 0.033 | 0.053 | -0.092 | -0.031 | 0.1 | -0.0031 | -0.024 | -0.023 | -0.026 | -0.0084 | 0.038 | -0.037 | -0.038 | 0.022 | 0.073 | -0.072 | 0.0063 | 0.0075 | -0.002 | 0.0043 | -0.0017 | 0.033 | 0.014 | -0.015 | 0.11 | 0.063 | -0.066 | -0.0029 | nan | -0.0027 | -0.0042 | 0.00078 | -0.045 | 0.0062 | 0.022 | -0.043 | -0.087 | 0.067 | -0.073 | -0.052 | -0.028 | -0.04 | -0.063 | -0.047 | -0.032 | -0.043 | -0.036 | -0.088 | -0.075 | 0.054 | 0.041 | 0.033 | 0.028 | 0.037 | 0.025 | 0.039 | 0.039 | 0.034 | 0.056 | 0.045 | -0.5 | 0.81 | 0.97 | -0.52 | 0.8 | 0.97 | -0.53 | 0.83 | 1 | -0.51 | 0.79 | 0.96 | -0.46 | 0.81 | 0.97 | -0.51 | 0.8 | 0.96 | -0.52 | 0.8 | 0.96 | -0.48 | 0.79 | 0.95 | -0.55 | 0.81 | 0.97 | -0.54 | 0.81 | 0.97 |
| LBH | 0.07 | 0.064 | 0.064 | 0.0073 | 0.072 | 0.048 | -0.031 | -0.26 | 0.29 | -0.0023 | -0.019 | -0.01 | -0.016 | -0.002 | 0.022 | -0.029 | -0.03 | 0.025 | 0.045 | -0.053 | -0.0012 | 0.031 | 0.016 | 0.00015 | 0.01 | -0.017 | 0.034 | 0.053 | -0.074 | -0.051 | 0.1 | -0.0028 | -0.0015 | -0.002 | -0.0071 | -0.008 | -0.017 | 0.018 | 0.023 | -0.037 | -0.06 | 0.043 | -0.0031 | nan | -0.00017 | 0.0005 | -0.0089 | 0.057 | 0.03 | -0.012 | 0.095 | 0.074 | -0.078 | 0.069 | 0.059 | 0.048 | 0.061 | 0.074 | 0.07 | 0.065 | 0.06 | 0.046 | 0.088 | 0.082 | -0.06 | -0.023 | -0.012 | -0.0072 | -0.029 | -0.0054 | -0.0076 | -0.017 | -0.023 | -0.062 | -0.05 | 0.99 | 0.012 | -0.48 | 0.98 | 0.014 | -0.49 | 0.98 | -0.00081 | -0.51 | 1 | 0.013 | -0.48 | 0.99 | 0.024 | -0.44 | 0.98 | 0.0049 | -0.47 | 0.98 | -0.034 | -0.5 | 0.98 | 0.012 | -0.44 | 0.99 | -0.041 | -0.54 | 0.99 | -0.046 | -0.52 |
| LBD | 0.12 | 0.1 | 0.1 | 0.038 | 0.15 | -0.022 | 0.016 | 0.26 | -0.072 | 0.0065 | 0.012 | -0.0021 | -0.025 | 0.019 | 0.023 | 0.037 | 0.025 | -0.11 | 0.0098 | 0.077 | -0.0062 | -0.014 | -0.021 | -0.045 | 0.011 | 0.051 | -0.0079 | -0.03 | -0.033 | 0.059 | -0.022 | 0.005 | 0.0077 | -0.0021 | -0.00054 | -0.015 | 0.045 | 0.037 | 0.038 | 0.12 | 0.02 | -0.03 | -0.0062 | nan | -0.0054 | -0.0067 | -0.019 | -0.016 | 0.027 | 0.052 | 0.02 | -0.057 | 0.039 | -0.013 | 0.016 | 0.028 | 0.017 | 0.007 | 0.022 | 0.038 | 0.022 | 0.027 | -0.015 | -0.0053 | 0.06 | 0.076 | 0.062 | 0.066 | 0.058 | 0.059 | 0.076 | 0.069 | 0.068 | 0.066 | 0.055 | 0.015 | 0.97 | 0.81 | -0.00041 | 0.96 | 0.8 | -0.013 | 0.95 | 0.79 | 0.013 | 1 | 0.82 | 0.069 | 0.98 | 0.82 | 0.013 | 0.95 | 0.82 | -0.021 | 0.96 | 0.81 | 0.037 | 0.97 | 0.83 | -0.046 | 0.96 | 0.8 | -0.04 | 0.96 | 0.81 |
| LBA | 0.045 | 0.038 | 0.038 | 0.014 | 0.054 | -0.034 | 0.046 | 0.35 | -0.23 | 0.0069 | 0.027 | 0.012 | -0.0049 | 0.0055 | -7.2e-05 | 0.031 | 0.052 | -0.089 | -0.026 | 0.096 | -0.0039 | -0.023 | -0.022 | -0.034 | -0.0071 | 0.04 | -0.04 | -0.037 | 0.023 | 0.072 | -0.071 | 0.0059 | 0.0076 | -0.0018 | 0.0045 | 0.0016 | 0.041 | 0.023 | -0.0069 | 0.1 | 0.056 | -0.06 | -0.0035 | nan | -0.0035 | -0.0048 | -0.00084 | -0.044 | 0.01 | 0.023 | -0.044 | -0.085 | 0.065 | -0.061 | -0.038 | -0.013 | -0.025 | -0.046 | -0.025 | -0.015 | -0.023 | -0.018 | -0.069 | -0.058 | 0.072 | 0.062 | 0.049 | 0.044 | 0.051 | 0.041 | 0.058 | 0.056 | 0.054 | 0.076 | 0.061 | -0.47 | 0.82 | 0.97 | -0.48 | 0.82 | 0.96 | -0.5 | 0.82 | 0.96 | -0.48 | 0.82 | 1 | -0.42 | 0.83 | 0.98 | -0.47 | 0.81 | 0.96 | -0.51 | 0.81 | 0.96 | -0.45 | 0.82 | 0.96 | -0.54 | 0.81 | 0.97 | -0.53 | 0.81 | 0.98 |
| PSH | 0.079 | 0.079 | 0.079 | 0.0092 | 0.027 | 0.052 | -0.04 | -0.25 | 0.3 | -0.0047 | -0.026 | -0.014 | -0.018 | 0.0035 | 0.038 | -0.038 | -0.022 | 0.028 | 0.03 | -0.037 | -0.0047 | 0.037 | 0.014 | 0.0029 | 0.004 | -0.049 | 0.0078 | 0.063 | -0.061 | -0.047 | 0.097 | -0.0047 | nan | nan | -0.0083 | -0.014 | -0.051 | 0.013 | 0.00087 | -0.038 | -0.047 | 0.034 | -0.0047 | nan | nan | 0.0014 | -0.0061 | 0.078 | 0.044 | -0.038 | 0.078 | 0.07 | -0.088 | 0.065 | 0.026 | 0.027 | 0.045 | 0.055 | 0.041 | 0.045 | 0.04 | 0.019 | 0.071 | 0.07 | -0.11 | -0.057 | -0.028 | -0.034 | -0.062 | -0.035 | -0.037 | -0.045 | -0.065 | -0.1 | -0.083 | 0.99 | 0.072 | -0.43 | 0.98 | 0.073 | -0.44 | 0.97 | 0.066 | -0.46 | 0.99 | 0.069 | -0.42 | 1 | 0.054 | -0.41 | 0.99 | 0.067 | -0.42 | 0.99 | 0.023 | -0.45 | 0.99 | 0.065 | -0.4 | 0.99 | 0.033 | -0.5 | 0.99 | 0.0056 | -0.49 |
| PSD | 0.12 | 0.12 | 0.12 | 0.031 | 0.028 | -0.031 | 0.013 | 0.27 | -0.074 | -0.0022 | 0.011 | -0.016 | -0.026 | 0.025 | 0.008 | 0.0052 | 0.043 | -0.11 | 0.0057 | 0.088 | -0.0022 | -0.029 | -0.034 | -0.049 | 0.03 | 0.05 | -0.023 | -0.02 | -0.021 | 0.036 | -0.0021 | -0.0022 | nan | nan | 0.0041 | -0.023 | 0.039 | 0.049 | -0.002 | 0.11 | 0.031 | -0.052 | -0.0022 | nan | nan | -0.0063 | -0.037 | -0.048 | 0.016 | 0.016 | 0.008 | -0.033 | 0.0097 | -0.07 | -0.049 | -0.012 | -0.035 | -0.059 | -0.037 | -0.014 | -0.029 | -0.043 | -0.073 | -0.065 | 0.022 | 0.019 | 0.014 | 0.022 | -0.0081 | -0.0018 | 0.029 | 0.016 | 0.0029 | 0.018 | 0.00098 | 0.033 | 0.98 | 0.83 | 0.018 | 0.97 | 0.81 | 0.0047 | 0.95 | 0.81 | 0.024 | 0.98 | 0.83 | 0.054 | 1 | 0.83 | 0.025 | 0.97 | 0.84 | -0.013 | 0.98 | 0.85 | 0.049 | 0.99 | 0.85 | 0.0018 | 0.97 | 0.8 | -0.016 | 0.98 | 0.82 |
| PSA | 0.052 | 0.049 | 0.049 | 0.0038 | 0.014 | -0.044 | 0.051 | 0.35 | -0.23 | 0.0015 | 0.032 | 0.01 | 0.0041 | -0.0093 | -0.00014 | 0.024 | 0.041 | -0.081 | -0.014 | 0.078 | 0.0015 | -0.033 | -0.027 | -0.031 | -0.0033 | 0.075 | -0.03 | -0.044 | 0.031 | 0.05 | -0.06 | 0.0015 | nan | nan | 0.014 | 0.014 | 0.044 | 0.03 | 0.003 | 0.093 | 0.045 | -0.055 | 0.0015 | nan | nan | -0.005 | -0.005 | -0.089 | -0.0064 | 0.027 | -0.05 | -0.064 | 0.054 | -0.1 | -0.071 | -0.031 | -0.053 | -0.085 | -0.054 | -0.047 | -0.045 | -0.054 | -0.1 | -0.095 | 0.067 | 0.037 | 0.016 | 0.019 | 0.022 | 0.012 | 0.037 | 0.033 | 0.029 | 0.058 | 0.038 | -0.43 | 0.83 | 0.98 | -0.45 | 0.83 | 0.98 | -0.46 | 0.83 | 0.97 | -0.44 | 0.82 | 0.98 | -0.41 | 0.83 | 1 | -0.44 | 0.82 | 0.98 | -0.46 | 0.84 | 0.98 | -0.42 | 0.83 | 0.98 | -0.49 | 0.82 | 0.98 | -0.5 | 0.84 | 0.98 |
| WHH | 0.066 | 0.06 | 0.06 | 0.013 | 0.063 | 0.041 | -0.032 | -0.26 | 0.29 | -0.0027 | -0.018 | -0.011 | -0.016 | -0.0033 | 0.025 | -0.028 | -0.034 | 0.029 | 0.047 | -0.059 | -0.0014 | 0.031 | 0.015 | 0.003 | 0.0079 | -0.015 | 0.034 | 0.053 | -0.075 | -0.049 | 0.1 | -0.0033 | -0.0019 | -0.0015 | -0.0067 | -0.0061 | -0.023 | 0.013 | 0.023 | -0.043 | -0.064 | 0.048 | -0.0033 | nan | -0.00034 | 0.00022 | -0.006 | 0.053 | 0.026 | -0.013 | 0.093 | 0.072 | -0.076 | 0.058 | 0.049 | 0.038 | 0.053 | 0.066 | 0.059 | 0.057 | 0.053 | 0.036 | 0.08 | 0.071 | -0.066 | -0.031 | -0.019 | -0.014 | -0.034 | -0.017 | -0.016 | -0.027 | -0.031 | -0.069 | -0.057 | 0.99 | 0.014 | -0.48 | 0.98 | 0.016 | -0.49 | 0.98 | 0.0022 | -0.51 | 0.98 | 0.013 | -0.47 | 0.99 | 0.025 | -0.44 | 1 | 0.0038 | -0.47 | 0.99 | -0.025 | -0.49 | 0.99 | 0.013 | -0.44 | 0.99 | -0.032 | -0.53 | 0.99 | -0.039 | -0.51 |
| WHD | 0.11 | 0.1 | 0.1 | 0.032 | 0.076 | -0.021 | 0.019 | 0.27 | -0.072 | 0.0033 | -0.0013 | -0.012 | -0.028 | 0.029 | 0.012 | 0.024 | 0.043 | -0.1 | -0.012 | 0.1 | -0.0053 | -0.025 | -0.03 | -0.046 | 0.021 | 0.039 | -0.016 | -0.013 | -0.034 | 0.043 | 0.002 | 0.0025 | 0.004 | -0.0029 | -0.00029 | -0.024 | 0.046 | 0.044 | 0.016 | 0.12 | 0.046 | -0.058 | -0.0053 | nan | -0.0047 | -0.0056 | -0.027 | -0.012 | 0.032 | 0.033 | 0.026 | -0.038 | 0.014 | -0.029 | -0.0058 | 0.017 | 0.0045 | -0.013 | 0.0049 | 0.024 | 0.0047 | 0.0061 | -0.035 | -0.015 | 0.042 | 0.054 | 0.052 | 0.049 | 0.041 | 0.042 | 0.06 | 0.051 | 0.048 | 0.048 | 0.044 | 0.012 | 0.96 | 0.81 | -0.0042 | 0.96 | 0.8 | -0.018 | 0.95 | 0.8 | 0.0049 | 0.95 | 0.81 | 0.067 | 0.97 | 0.82 | 0.0038 | 1 | 0.82 | -0.017 | 0.96 | 0.82 | 0.032 | 0.96 | 0.83 | -0.04 | 0.96 | 0.8 | -0.034 | 0.97 | 0.81 |
| WHA | 0.044 | 0.039 | 0.039 | 0.016 | 0.029 | -0.035 | 0.033 | 0.35 | -0.22 | 0.0075 | 0.022 | 0.0049 | -0.0021 | 0.0057 | 0.003 | 0.032 | 0.049 | -0.088 | -0.026 | 0.095 | -0.0033 | -0.026 | -0.026 | -0.03 | -0.0071 | 0.041 | -0.038 | -0.045 | 0.029 | 0.075 | -0.078 | 0.007 | 0.0076 | -0.0022 | 0.0045 | 0.0022 | 0.035 | 0.019 | -0.0062 | 0.1 | 0.054 | -0.058 | -0.0023 | nan | -0.0033 | -0.0046 | -0.00099 | -0.05 | 0.0046 | 0.028 | -0.052 | -0.09 | 0.069 | -0.072 | -0.053 | -0.031 | -0.042 | -0.063 | -0.046 | -0.032 | -0.041 | -0.034 | -0.085 | -0.075 | 0.052 | 0.04 | 0.031 | 0.031 | 0.037 | 0.025 | 0.037 | 0.037 | 0.034 | 0.057 | 0.041 | -0.46 | 0.83 | 0.97 | -0.48 | 0.82 | 0.97 | -0.49 | 0.83 | 0.96 | -0.47 | 0.82 | 0.96 | -0.42 | 0.84 | 0.98 | -0.47 | 0.82 | 1 | -0.49 | 0.83 | 0.97 | -0.44 | 0.82 | 0.97 | -0.52 | 0.82 | 0.97 | -0.51 | 0.83 | 0.98 |
| SJH | 0.056 | 0.054 | 0.054 | 0.005 | 0.029 | 0.024 | -0.017 | -0.25 | 0.29 | -0.0085 | -0.02 | -0.013 | -0.016 | 0.00054 | -7.8e-05 | -0.033 | -0.019 | 0.029 | 0.041 | -0.049 | -0.002 | 0.0051 | 0.0019 | 0.0041 | 0.021 | -0.018 | 0.03 | 0.059 | -0.069 | -0.059 | 0.11 | -0.0086 | -0.0076 | -0.0024 | -0.0082 | -0.0086 | -0.0017 | 0.02 | 0.014 | -0.039 | -0.052 | 0.029 | -0.0043 | nan | -0.00079 | 0.00018 | -0.016 | 0.044 | 0.018 | -0.023 | 0.091 | 0.082 | -0.083 | 0.032 | 0.054 | 0.037 | 0.048 | 0.051 | 0.062 | 0.042 | 0.041 | 0.031 | 0.071 | 0.054 | -0.054 | -0.037 | -0.044 | -0.036 | -0.041 | -0.045 | -0.027 | -0.051 | -0.026 | -0.08 | -0.065 | 0.99 | -0.016 | -0.49 | 0.99 | -0.01 | -0.51 | 0.98 | -0.029 | -0.52 | 0.98 | -0.021 | -0.51 | 0.99 | -0.013 | -0.46 | 0.99 | -0.017 | -0.49 | 1 | -0.02 | -0.49 | 0.99 | -0.016 | -0.46 | 0.99 | -0.025 | -0.52 | 0.99 | -0.032 | -0.51 |
| SJD | 0.098 | 0.09 | 0.09 | 0.031 | 0.088 | -0.015 | 0.0075 | 0.27 | -0.076 | 0.0035 | -0.024 | -0.025 | -0.025 | 0.042 | 0.0069 | 0.04 | 0.021 | -0.09 | -0.0092 | 0.086 | -0.0058 | -0.036 | -0.03 | -0.032 | 0.024 | 0.029 | 0.0018 | -0.03 | -0.035 | 0.056 | -0.02 | 0.0027 | 0.0043 | -0.002 | 1.3e-05 | -0.034 | 0.039 | 0.016 | 0.026 | 0.1 | 0.038 | -0.047 | -0.0057 | nan | -0.0051 | -0.0072 | -0.028 | -0.0033 | 0.016 | 0.051 | 0.025 | -0.054 | 0.031 | -0.023 | -0.0085 | -0.0059 | -0.014 | -0.016 | -0.01 | 0.0088 | -0.0037 | 0.0028 | -0.043 | -0.026 | 0.034 | 0.042 | 0.051 | 0.039 | 0.041 | 0.037 | 0.046 | 0.045 | 0.055 | 0.046 | 0.04 | -0.022 | 0.97 | 0.82 | -0.035 | 0.97 | 0.8 | -0.049 | 0.96 | 0.8 | -0.034 | 0.96 | 0.81 | 0.023 | 0.98 | 0.84 | -0.025 | 0.96 | 0.83 | -0.02 | 1 | 0.83 | -0.0045 | 0.96 | 0.84 | -0.044 | 0.97 | 0.81 | -0.04 | 0.97 | 0.82 |
| SJA | 0.033 | 0.032 | 0.032 | 0.012 | -0.0076 | -0.02 | 0.016 | 0.35 | -0.22 | 0.0068 | -0.00043 | -0.0072 | -0.0039 | 0.019 | -0.0039 | 0.032 | 0.049 | -0.081 | -0.035 | 0.1 | -0.0035 | -0.022 | -0.021 | -0.018 | -0.009 | 0.022 | -0.033 | -0.038 | 0.021 | 0.081 | -0.079 | 0.0063 | 0.0068 | -0.0024 | 0.0049 | -0.0097 | 0.029 | 0.0047 | -0.02 | 0.096 | 0.062 | -0.065 | -0.0026 | nan | -0.0035 | -0.0052 | 0.0027 | -0.028 | 0.0056 | 0.024 | -0.044 | -0.095 | 0.067 | -0.062 | -0.068 | -0.052 | -0.057 | -0.067 | -0.068 | -0.043 | -0.058 | -0.041 | -0.098 | -0.078 | 0.027 | 0.023 | 0.043 | 0.029 | 0.027 | 0.027 | 0.025 | 0.031 | 0.026 | 0.052 | 0.041 | -0.49 | 0.83 | 0.98 | -0.5 | 0.82 | 0.97 | -0.51 | 0.82 | 0.96 | -0.5 | 0.81 | 0.96 | -0.45 | 0.85 | 0.98 | -0.49 | 0.82 | 0.97 | -0.49 | 0.83 | 1 | -0.47 | 0.82 | 0.97 | -0.51 | 0.83 | 0.98 | -0.5 | 0.83 | 0.98 |
| VCH | 0.075 | 0.069 | 0.069 | 0.0097 | 0.068 | 0.047 | -0.03 | -0.25 | 0.29 | -0.0013 | -0.016 | -0.0097 | -0.016 | -0.0032 | 0.028 | -0.023 | -0.032 | 0.019 | 0.046 | -0.052 | -0.0017 | 0.03 | 0.016 | 0.0032 | 0.0064 | -0.013 | 0.034 | 0.057 | -0.079 | -0.05 | 0.11 | -0.002 | -0.00033 | -0.0018 | -0.0066 | -0.0066 | -0.022 | 0.012 | 0.026 | -0.032 | -0.06 | 0.045 | -0.0036 | nan | -0.00061 | 0.00011 | -0.0052 | 0.054 | 0.029 | -0.015 | 0.1 | 0.075 | -0.08 | 0.065 | 0.053 | 0.046 | 0.058 | 0.07 | 0.065 | 0.063 | 0.057 | 0.042 | 0.084 | 0.08 | -0.062 | -0.025 | -0.015 | -0.0095 | -0.03 | -0.011 | -0.0096 | -0.021 | -0.026 | -0.065 | -0.051 | 0.99 | 0.039 | -0.45 | 0.98 | 0.04 | -0.47 | 0.97 | 0.026 | -0.48 | 0.98 | 0.037 | -0.45 | 0.99 | 0.049 | -0.42 | 0.99 | 0.032 | -0.44 | 0.99 | -0.0045 | -0.47 | 1 | 0.038 | -0.42 | 0.98 | -0.006 | -0.51 | 0.98 | -0.013 | -0.49 |
| VCD | 0.12 | 0.11 | 0.11 | 0.036 | 0.15 | -0.019 | 0.019 | 0.27 | -0.07 | 0.0059 | 0.0095 | -0.0074 | -0.029 | 0.023 | 0.032 | 0.043 | 0.027 | -0.12 | 0.012 | 0.088 | -0.004 | -0.02 | -0.023 | -0.048 | 0.018 | 0.06 | 0.0044 | -0.032 | -0.052 | 0.062 | -0.012 | 0.0051 | 0.0064 | -0.0027 | -0.00068 | -0.02 | 0.038 | 0.035 | 0.037 | 0.13 | 0.023 | -0.034 | -0.0038 | nan | -0.0035 | -0.0048 | -0.025 | -0.022 | 0.02 | 0.057 | 0.04 | -0.056 | 0.037 | -0.0092 | 0.02 | 0.039 | 0.025 | 0.013 | 0.028 | 0.045 | 0.028 | 0.031 | -0.0081 | 0.0046 | 0.065 | 0.081 | 0.074 | 0.075 | 0.066 | 0.065 | 0.082 | 0.074 | 0.074 | 0.077 | 0.064 | 0.017 | 0.98 | 0.81 | 0.0013 | 0.97 | 0.8 | -0.013 | 0.95 | 0.79 | 0.012 | 0.97 | 0.82 | 0.065 | 0.99 | 0.83 | 0.013 | 0.96 | 0.82 | -0.016 | 0.96 | 0.82 | 0.038 | 1 | 0.84 | -0.037 | 0.97 | 0.8 | -0.032 | 0.97 | 0.81 |
| VCA | 0.056 | 0.05 | 0.05 | 0.017 | 0.045 | -0.033 | 0.037 | 0.34 | -0.22 | 0.0073 | 0.027 | 0.0052 | -0.0034 | 0.0032 | 0.0033 | 0.033 | 0.056 | -0.095 | -0.027 | 0.1 | -0.0028 | -0.022 | -0.02 | -0.034 | -0.0071 | 0.047 | -0.029 | -0.042 | 0.015 | 0.074 | -0.07 | 0.0068 | 0.0074 | -0.0017 | 0.0061 | 0.0038 | 0.038 | 0.023 | -0.0097 | 0.11 | 0.058 | -0.064 | -0.0018 | nan | -0.0029 | -0.0042 | -0.00061 | -0.05 | 0.0026 | 0.031 | -0.037 | -0.086 | 0.066 | -0.066 | -0.044 | -0.02 | -0.03 | -0.053 | -0.034 | -0.023 | -0.029 | -0.026 | -0.077 | -0.061 | 0.064 | 0.051 | 0.041 | 0.04 | 0.045 | 0.034 | 0.046 | 0.048 | 0.045 | 0.069 | 0.053 | -0.44 | 0.84 | 0.97 | -0.45 | 0.84 | 0.97 | -0.46 | 0.84 | 0.95 | -0.44 | 0.83 | 0.96 | -0.4 | 0.85 | 0.98 | -0.44 | 0.83 | 0.97 | -0.46 | 0.84 | 0.97 | -0.42 | 0.84 | 1 | -0.49 | 0.84 | 0.97 | -0.49 | 0.84 | 0.97 |
| GBH | 0.051 | 0.05 | 0.05 | 0.0059 | 0.025 | 0.018 | -0.012 | -0.26 | 0.3 | -0.0056 | -0.019 | -0.014 | -0.014 | -0.00022 | 0.0017 | -0.029 | -0.025 | 0.031 | 0.041 | -0.057 | -0.0021 | 0.004 | 0.0038 | 0.0047 | 0.02 | -0.0083 | 0.041 | 0.056 | -0.074 | -0.065 | 0.12 | -0.0062 | -0.0045 | -0.0023 | -0.0046 | -0.0065 | -0.00091 | 0.017 | 0.021 | -0.043 | -0.054 | 0.038 | -0.0048 | nan | -0.00059 | -0.00059 | -0.013 | 0.035 | 0.011 | -0.021 | 0.099 | 0.089 | -0.085 | 0.036 | 0.06 | 0.043 | 0.042 | 0.044 | 0.072 | 0.047 | 0.061 | 0.03 | 0.063 | 0.056 | -0.056 | -0.05 | -0.053 | -0.038 | -0.031 | -0.061 | -0.027 | -0.05 | -0.015 | -0.09 | -0.068 | 0.99 | -0.038 | -0.52 | 0.99 | -0.032 | -0.54 | 0.99 | -0.059 | -0.55 | 0.99 | -0.046 | -0.54 | 0.99 | 0.0018 | -0.49 | 0.99 | -0.04 | -0.52 | 0.99 | -0.044 | -0.51 | 0.98 | -0.037 | -0.49 | 1 | -0.042 | -0.54 | 0.99 | -0.049 | -0.52 |
| GBD | 0.095 | 0.088 | 0.088 | 0.033 | 0.11 | -0.0087 | 0.0087 | 0.27 | -0.069 | 0.0038 | -0.0099 | -0.012 | -0.02 | 0.029 | 0.0044 | 0.049 | 0.018 | -0.075 | -0.019 | 0.078 | -0.006 | -0.031 | -0.032 | -0.031 | 0.013 | 0.027 | -0.0039 | -0.027 | -0.028 | 0.058 | -0.027 | 0.0032 | 0.0043 | -0.0039 | -0.0068 | -0.02 | 0.04 | 0.01 | 0.03 | 0.088 | 0.039 | -0.042 | -0.0057 | nan | -0.0054 | -0.0054 | -0.015 | 0.0029 | 0.023 | 0.054 | 0.018 | -0.058 | 0.036 | -0.015 | -0.0067 | -0.0084 | -0.019 | -0.0046 | -0.0018 | 0.023 | -0.011 | 0.025 | -0.048 | -0.033 | 0.034 | 0.057 | 0.068 | 0.047 | 0.059 | 0.061 | 0.052 | 0.045 | 0.054 | 0.056 | 0.056 | -0.026 | 0.98 | 0.82 | -0.039 | 0.98 | 0.81 | -0.057 | 0.96 | 0.81 | -0.041 | 0.96 | 0.81 | 0.033 | 0.97 | 0.82 | -0.032 | 0.96 | 0.82 | -0.025 | 0.97 | 0.83 | -0.006 | 0.97 | 0.84 | -0.042 | 1 | 0.82 | -0.038 | 0.98 | 0.83 |
| GBA | 0.025 | 0.023 | 0.023 | 0.012 | 0.016 | -0.011 | 0.026 | 0.35 | -0.23 | 0.0084 | 0.01 | 0.00092 | -0.0013 | 0.012 | -0.0024 | 0.041 | 0.051 | -0.076 | -0.045 | 0.1 | -0.004 | -0.017 | -0.024 | -0.019 | -0.015 | 0.018 | -0.038 | -0.032 | 0.022 | 0.082 | -0.087 | 0.0079 | 0.0082 | -0.0027 | -0.0036 | -0.003 | 0.022 | -0.0061 | -0.027 | 0.092 | 0.068 | -0.064 | -0.0023 | nan | -0.0041 | -0.0041 | 0.01 | -0.023 | 0.0097 | 0.019 | -0.047 | -0.097 | 0.071 | -0.055 | -0.065 | -0.049 | -0.051 | -0.051 | -0.058 | -0.029 | -0.065 | -0.019 | -0.096 | -0.078 | 0.036 | 0.05 | 0.068 | 0.044 | 0.042 | 0.064 | 0.034 | 0.039 | 0.027 | 0.069 | 0.066 | -0.52 | 0.82 | 0.98 | -0.54 | 0.81 | 0.98 | -0.55 | 0.82 | 0.97 | -0.54 | 0.8 | 0.97 | -0.5 | 0.8 | 0.98 | -0.53 | 0.8 | 0.97 | -0.52 | 0.81 | 0.98 | -0.51 | 0.8 | 0.97 | -0.54 | 0.82 | 1 | -0.53 | 0.82 | 0.98 |
| BSH | 0.049 | 0.048 | 0.048 | 0.0095 | 0.027 | 0.018 | -0.012 | -0.25 | 0.3 | -0.0064 | -0.019 | -0.015 | -0.014 | 0.00082 | -0.0042 | -0.034 | -0.021 | 0.036 | 0.037 | -0.055 | -0.002 | 0.0032 | 0.0034 | 0.0037 | 0.02 | -0.011 | 0.038 | 0.058 | -0.071 | -0.066 | 0.12 | -0.0068 | -0.0054 | -0.0026 | -0.0046 | -0.007 | 0.0039 | 0.021 | 0.018 | -0.047 | -0.051 | 0.034 | -0.0045 | nan | -0.0007 | -0.0007 | -0.014 | 0.038 | 0.014 | -0.021 | 0.096 | 0.089 | -0.086 | 0.03 | 0.06 | 0.039 | 0.04 | 0.042 | 0.071 | 0.047 | 0.057 | 0.033 | 0.063 | 0.054 | -0.052 | -0.051 | -0.054 | -0.038 | -0.031 | -0.057 | -0.024 | -0.047 | -0.016 | -0.088 | -0.067 | 0.99 | -0.033 | -0.51 | 0.99 | -0.027 | -0.53 | 0.98 | -0.055 | -0.54 | 0.99 | -0.04 | -0.53 | 0.99 | -0.016 | -0.5 | 0.99 | -0.034 | -0.51 | 0.99 | -0.04 | -0.5 | 0.98 | -0.032 | -0.49 | 0.99 | -0.038 | -0.53 | 1 | -0.044 | -0.52 |
| BSD | 0.096 | 0.089 | 0.089 | 0.034 | 0.11 | -0.0067 | 0.011 | 0.27 | -0.073 | 0.0049 | -0.012 | -0.014 | -0.022 | 0.031 | -0.00098 | 0.043 | 0.026 | -0.076 | -0.023 | 0.086 | -0.0061 | -0.031 | -0.029 | -0.03 | 0.014 | 0.022 | -0.008 | -0.022 | -0.026 | 0.056 | -0.023 | 0.004 | 0.0056 | -0.0026 | -0.0056 | -0.023 | 0.046 | 0.017 | 0.025 | 0.091 | 0.045 | -0.048 | -0.0056 | nan | -0.0055 | -0.0055 | -0.017 | 0.0063 | 0.026 | 0.048 | 0.018 | -0.056 | 0.031 | -0.015 | -0.0032 | -0.00082 | -0.018 | -0.00015 | 0.0071 | 0.027 | -0.0091 | 0.028 | -0.047 | -0.028 | 0.036 | 0.061 | 0.073 | 0.047 | 0.062 | 0.068 | 0.058 | 0.046 | 0.059 | 0.06 | 0.06 | -0.033 | 0.98 | 0.83 | -0.048 | 0.97 | 0.81 | -0.065 | 0.96 | 0.81 | -0.046 | 0.96 | 0.81 | 0.0056 | 0.98 | 0.84 | -0.039 | 0.97 | 0.83 | -0.032 | 0.97 | 0.83 | -0.013 | 0.97 | 0.84 | -0.049 | 0.98 | 0.82 | -0.044 | 1 | 0.83 |
| BSA | 0.024 | 0.022 | 0.022 | 0.013 | 0.013 | -0.011 | 0.021 | 0.35 | -0.22 | 0.0088 | 0.0076 | -0.00077 | -0.0042 | 0.016 | -0.014 | 0.032 | 0.057 | -0.07 | -0.049 | 0.11 | -0.0041 | -0.017 | -0.023 | -0.02 | -0.011 | 0.00056 | -0.054 | -0.023 | 0.031 | 0.082 | -0.084 | 0.0081 | 0.0089 | -0.0024 | -0.0039 | -0.0065 | 0.033 | 0.0037 | -0.031 | 0.087 | 0.071 | -0.069 | -0.0029 | nan | -0.0041 | -0.0041 | 0.0063 | -0.009 | 0.023 | 0.011 | -0.053 | -0.097 | 0.067 | -0.052 | -0.065 | -0.05 | -0.054 | -0.052 | -0.058 | -0.03 | -0.063 | -0.025 | -0.097 | -0.078 | 0.03 | 0.042 | 0.059 | 0.035 | 0.036 | 0.059 | 0.031 | 0.032 | 0.024 | 0.064 | 0.055 | -0.51 | 0.83 | 0.98 | -0.52 | 0.82 | 0.97 | -0.54 | 0.83 | 0.97 | -0.52 | 0.81 | 0.98 | -0.49 | 0.82 | 0.98 | -0.51 | 0.81 | 0.98 | -0.51 | 0.82 | 0.98 | -0.49 | 0.81 | 0.97 | -0.52 | 0.83 | 0.98 | -0.52 | 0.83 | 1 |
matches NULLs:
id 0
country_id 0
league_id 0
season 0
stage 0
...
GBD 11817
GBA 11817
BSH 11818
BSD 11818
BSA 11818
Length: 115, dtype: int64
Found df matches with nulls..... ================================================== players ================================================== players INFO: <class 'pandas.core.frame.DataFrame'> RangeIndex: 11060 entries, 0 to 11059 Data columns (total 7 columns): id 11060 non-null int64 player_api_id 11060 non-null int64 player_name 11060 non-null object player_fifa_api_id 11060 non-null int64 birthday 11060 non-null object height 11060 non-null float64 weight 11060 non-null int64 dtypes: float64(1), int64(4), object(2) memory usage: 605.0+ KB
None
players Describtion:
| count | mean | std | min | 25% | 50% | 75% | max | |
|---|---|---|---|---|---|---|---|---|
| id | 11060.0 | 5537.511392 | 3197.692647 | 1.00 | 2767.75 | 5536.50 | 8306.25 | 11075.00 |
| player_api_id | 11060.0 | 156582.427215 | 160713.700624 | 2625.00 | 35555.50 | 96619.50 | 212470.50 | 750584.00 |
| player_fifa_api_id | 11060.0 | 165664.910488 | 58649.928360 | 2.00 | 151889.50 | 184671.00 | 203883.25 | 234141.00 |
| height | 11060.0 | 181.867445 | 6.369201 | 157.48 | 177.80 | 182.88 | 185.42 | 208.28 |
| weight | 11060.0 | 168.380289 | 14.990217 | 117.00 | 159.00 | 168.00 | 179.00 | 243.00 |
players Correlations:
| id | player_api_id | player_fifa_api_id | height | weight | |
|---|---|---|---|---|---|
| id | 1 | -0.0065 | -0.0024 | 0.0086 | 0.0047 |
| player_api_id | -0.0065 | 1 | 0.58 | -0.054 | -0.16 |
| player_fifa_api_id | -0.0024 | 0.58 | 1 | -0.026 | -0.11 |
| height | 0.0086 | -0.054 | -0.026 | 1 | 0.77 |
| weight | 0.0047 | -0.16 | -0.11 | 0.77 | 1 |
players NULLs:
id 0 player_api_id 0 player_name 0 player_fifa_api_id 0 birthday 0 height 0 weight 0 dtype: int64
================================================== player_attributes ================================================== player_attributes INFO: <class 'pandas.core.frame.DataFrame'> RangeIndex: 183978 entries, 0 to 183977 Data columns (total 42 columns): id 183978 non-null int64 player_fifa_api_id 183978 non-null int64 player_api_id 183978 non-null int64 date 183978 non-null object overall_rating 183142 non-null float64 potential 183142 non-null float64 preferred_foot 183142 non-null object attacking_work_rate 180748 non-null object defensive_work_rate 183142 non-null object crossing 183142 non-null float64 finishing 183142 non-null float64 heading_accuracy 183142 non-null float64 short_passing 183142 non-null float64 volleys 181265 non-null float64 dribbling 183142 non-null float64 curve 181265 non-null float64 free_kick_accuracy 183142 non-null float64 long_passing 183142 non-null float64 ball_control 183142 non-null float64 acceleration 183142 non-null float64 sprint_speed 183142 non-null float64 agility 181265 non-null float64 reactions 183142 non-null float64 balance 181265 non-null float64 shot_power 183142 non-null float64 jumping 181265 non-null float64 stamina 183142 non-null float64 strength 183142 non-null float64 long_shots 183142 non-null float64 aggression 183142 non-null float64 interceptions 183142 non-null float64 positioning 183142 non-null float64 vision 181265 non-null float64 penalties 183142 non-null float64 marking 183142 non-null float64 standing_tackle 183142 non-null float64 sliding_tackle 181265 non-null float64 gk_diving 183142 non-null float64 gk_handling 183142 non-null float64 gk_kicking 183142 non-null float64 gk_positioning 183142 non-null float64 gk_reflexes 183142 non-null float64 dtypes: float64(35), int64(3), object(4) memory usage: 59.0+ MB
None
player_attributes Describtion:
| count | mean | std | min | 25% | 50% | 75% | max | |
|---|---|---|---|---|---|---|---|---|
| id | 183978.0 | 91989.500000 | 53110.018250 | 1.0 | 45995.25 | 91989.5 | 137983.75 | 183978.0 |
| player_fifa_api_id | 183978.0 | 165671.524291 | 53851.094769 | 2.0 | 155798.00 | 183488.0 | 199848.00 | 234141.0 |
| player_api_id | 183978.0 | 135900.617324 | 136927.840510 | 2625.0 | 34763.00 | 77741.0 | 191080.00 | 750584.0 |
| overall_rating | 183142.0 | 68.600015 | 7.041139 | 33.0 | 64.00 | 69.0 | 73.00 | 94.0 |
| potential | 183142.0 | 73.460353 | 6.592271 | 39.0 | 69.00 | 74.0 | 78.00 | 97.0 |
| crossing | 183142.0 | 55.086883 | 17.242135 | 1.0 | 45.00 | 59.0 | 68.00 | 95.0 |
| finishing | 183142.0 | 49.921078 | 19.038705 | 1.0 | 34.00 | 53.0 | 65.00 | 97.0 |
| heading_accuracy | 183142.0 | 57.266023 | 16.488905 | 1.0 | 49.00 | 60.0 | 68.00 | 98.0 |
| short_passing | 183142.0 | 62.429672 | 14.194068 | 3.0 | 57.00 | 65.0 | 72.00 | 97.0 |
| volleys | 181265.0 | 49.468436 | 18.256618 | 1.0 | 35.00 | 52.0 | 64.00 | 93.0 |
| dribbling | 183142.0 | 59.175154 | 17.744688 | 1.0 | 52.00 | 64.0 | 72.00 | 97.0 |
| curve | 181265.0 | 52.965675 | 18.255788 | 2.0 | 41.00 | 56.0 | 67.00 | 94.0 |
| free_kick_accuracy | 183142.0 | 49.380950 | 17.831746 | 1.0 | 36.00 | 50.0 | 63.00 | 97.0 |
| long_passing | 183142.0 | 57.069880 | 14.394464 | 3.0 | 49.00 | 59.0 | 67.00 | 97.0 |
| ball_control | 183142.0 | 63.388879 | 15.196671 | 5.0 | 58.00 | 67.0 | 73.00 | 97.0 |
| acceleration | 183142.0 | 67.659357 | 12.983326 | 10.0 | 61.00 | 69.0 | 77.00 | 97.0 |
| sprint_speed | 183142.0 | 68.051244 | 12.569721 | 12.0 | 62.00 | 69.0 | 77.00 | 97.0 |
| agility | 181265.0 | 65.970910 | 12.954585 | 11.0 | 58.00 | 68.0 | 75.00 | 96.0 |
| reactions | 183142.0 | 66.103706 | 9.155408 | 17.0 | 61.00 | 67.0 | 72.00 | 96.0 |
| balance | 181265.0 | 65.189496 | 13.063188 | 12.0 | 58.00 | 67.0 | 74.00 | 96.0 |
| shot_power | 183142.0 | 61.808427 | 16.135143 | 2.0 | 54.00 | 65.0 | 73.00 | 97.0 |
| jumping | 181265.0 | 66.969045 | 11.006734 | 14.0 | 60.00 | 68.0 | 74.00 | 96.0 |
| stamina | 183142.0 | 67.038544 | 13.165262 | 10.0 | 61.00 | 69.0 | 76.00 | 96.0 |
| strength | 183142.0 | 67.424529 | 12.072280 | 10.0 | 60.00 | 69.0 | 76.00 | 96.0 |
| long_shots | 183142.0 | 53.339431 | 18.367025 | 1.0 | 41.00 | 58.0 | 67.00 | 96.0 |
| aggression | 183142.0 | 60.948046 | 16.089521 | 6.0 | 51.00 | 64.0 | 73.00 | 97.0 |
| interceptions | 183142.0 | 52.009271 | 19.450133 | 1.0 | 34.00 | 57.0 | 68.00 | 96.0 |
| positioning | 183142.0 | 55.786504 | 18.448292 | 2.0 | 45.00 | 60.0 | 69.00 | 96.0 |
| vision | 181265.0 | 57.873550 | 15.144086 | 1.0 | 49.00 | 60.0 | 69.00 | 97.0 |
| penalties | 183142.0 | 55.003986 | 15.546519 | 2.0 | 45.00 | 57.0 | 67.00 | 96.0 |
| marking | 183142.0 | 46.772242 | 21.227667 | 1.0 | 25.00 | 50.0 | 66.00 | 96.0 |
| standing_tackle | 183142.0 | 50.351257 | 21.483706 | 1.0 | 29.00 | 56.0 | 69.00 | 95.0 |
| sliding_tackle | 181265.0 | 48.001462 | 21.598778 | 2.0 | 25.00 | 53.0 | 67.00 | 95.0 |
| gk_diving | 183142.0 | 14.704393 | 16.865467 | 1.0 | 7.00 | 10.0 | 13.00 | 94.0 |
| gk_handling | 183142.0 | 16.063612 | 15.867382 | 1.0 | 8.00 | 11.0 | 15.00 | 93.0 |
| gk_kicking | 183142.0 | 20.998362 | 21.452980 | 1.0 | 8.00 | 12.0 | 15.00 | 97.0 |
| gk_positioning | 183142.0 | 16.132154 | 16.099175 | 1.0 | 8.00 | 11.0 | 15.00 | 96.0 |
| gk_reflexes | 183142.0 | 16.441439 | 17.198155 | 1.0 | 8.00 | 11.0 | 15.00 | 96.0 |
player_attributes Correlations:
| id | player_fifa_api_id | player_api_id | overall_rating | potential | crossing | finishing | heading_accuracy | short_passing | volleys | dribbling | curve | free_kick_accuracy | long_passing | ball_control | acceleration | sprint_speed | agility | reactions | balance | shot_power | jumping | stamina | strength | long_shots | aggression | interceptions | positioning | vision | penalties | marking | standing_tackle | sliding_tackle | gk_diving | gk_handling | gk_kicking | gk_positioning | gk_reflexes | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| id | 1 | 0.0034 | 0.002 | -0.0029 | 0.0012 | -0.019 | -0.0079 | -0.011 | -0.0061 | -0.0063 | -0.014 | -0.019 | -0.0076 | -0.0074 | -0.013 | -0.0076 | -0.011 | -0.00087 | -0.0042 | -0.0094 | -0.0097 | -0.0042 | -0.0098 | -0.0083 | -0.01 | -0.017 | -0.0077 | -0.015 | -0.0077 | -0.011 | -0.0096 | -0.012 | -0.011 | 0.014 | 0.01 | 0.0086 | 0.014 | 0.014 |
| player_fifa_api_id | 0.0034 | 1 | 0.55 | -0.27 | -0.028 | -0.064 | -0.028 | -0.1 | -0.064 | -0.088 | 0.05 | -0.051 | -0.11 | -0.11 | -0.023 | 0.18 | 0.18 | 0.12 | -0.23 | 0.0077 | -0.078 | -0.073 | 0.012 | -0.18 | -0.067 | -0.17 | -0.18 | -0.086 | -0.16 | -0.18 | -0.078 | -0.073 | -0.054 | -0.092 | -0.14 | -0.27 | -0.15 | -0.14 |
| player_api_id | 0.002 | 0.55 | 1 | -0.32 | 0.011 | -0.11 | -0.06 | -0.13 | -0.087 | -0.13 | 0.018 | -0.098 | -0.15 | -0.14 | -0.051 | 0.1 | 0.096 | 0.028 | -0.31 | 0.021 | -0.12 | -0.14 | -0.11 | -0.23 | -0.12 | -0.21 | -0.19 | -0.11 | -0.19 | -0.16 | -0.09 | -0.087 | -0.073 | -0.071 | -0.13 | -0.24 | -0.13 | -0.12 |
| overall_rating | -0.0029 | -0.27 | -0.32 | 1 | 0.77 | 0.36 | 0.33 | 0.31 | 0.46 | 0.36 | 0.35 | 0.36 | 0.35 | 0.44 | 0.44 | 0.25 | 0.25 | 0.24 | 0.77 | 0.16 | 0.43 | 0.26 | 0.33 | 0.32 | 0.39 | 0.32 | 0.25 | 0.37 | 0.43 | 0.39 | 0.13 | 0.17 | 0.13 | 0.028 | 0.0044 | 0.026 | 0.0057 | 0.0057 |
| potential | 0.0012 | -0.028 | 0.011 | 0.77 | 1 | 0.28 | 0.29 | 0.21 | 0.38 | 0.3 | 0.34 | 0.3 | 0.26 | 0.34 | 0.4 | 0.34 | 0.34 | 0.29 | 0.58 | 0.2 | 0.33 | 0.17 | 0.26 | 0.13 | 0.31 | 0.16 | 0.17 | 0.33 | 0.38 | 0.32 | 0.056 | 0.084 | 0.064 | -0.011 | 0.0047 | 0.089 | 0.0034 | 0.004 |
| crossing | -0.019 | -0.064 | -0.11 | 0.36 | 0.28 | 1 | 0.58 | 0.37 | 0.79 | 0.64 | 0.81 | 0.79 | 0.71 | 0.68 | 0.81 | 0.6 | 0.58 | 0.6 | 0.38 | 0.52 | 0.66 | 0.021 | 0.56 | -0.07 | 0.72 | 0.32 | 0.31 | 0.68 | 0.69 | 0.57 | 0.24 | 0.29 | 0.28 | -0.6 | -0.6 | -0.35 | -0.6 | -0.6 |
| finishing | -0.0079 | -0.028 | -0.06 | 0.33 | 0.29 | 0.58 | 1 | 0.37 | 0.58 | 0.85 | 0.78 | 0.69 | 0.63 | 0.34 | 0.72 | 0.53 | 0.51 | 0.55 | 0.35 | 0.39 | 0.73 | 0.009 | 0.35 | -0.053 | 0.81 | 0.044 | -0.15 | 0.8 | 0.65 | 0.72 | -0.28 | -0.23 | -0.26 | -0.48 | -0.47 | -0.29 | -0.47 | -0.47 |
| heading_accuracy | -0.011 | -0.1 | -0.13 | 0.31 | 0.21 | 0.37 | 0.37 | 1 | 0.55 | 0.39 | 0.4 | 0.32 | 0.31 | 0.36 | 0.55 | 0.2 | 0.27 | 0.069 | 0.3 | 0.079 | 0.54 | 0.29 | 0.48 | 0.49 | 0.41 | 0.58 | 0.45 | 0.41 | 0.34 | 0.43 | 0.46 | 0.48 | 0.44 | -0.67 | -0.65 | -0.39 | -0.65 | -0.65 |
| short_passing | -0.0061 | -0.064 | -0.087 | 0.46 | 0.38 | 0.79 | 0.58 | 0.55 | 1 | 0.64 | 0.79 | 0.73 | 0.69 | 0.8 | 0.89 | 0.5 | 0.49 | 0.51 | 0.46 | 0.46 | 0.72 | 0.06 | 0.61 | 0.092 | 0.73 | 0.45 | 0.42 | 0.68 | 0.77 | 0.61 | 0.35 | 0.42 | 0.38 | -0.69 | -0.69 | -0.41 | -0.69 | -0.69 |
| volleys | -0.0063 | -0.088 | -0.13 | 0.36 | 0.3 | 0.64 | 0.85 | 0.39 | 0.64 | 1 | 0.78 | 0.75 | 0.68 | 0.41 | 0.75 | 0.51 | 0.49 | 0.56 | 0.4 | 0.42 | 0.75 | 0.023 | 0.38 | -0.036 | 0.81 | 0.13 | -0.038 | 0.78 | 0.69 | 0.71 | -0.17 | -0.11 | -0.13 | -0.51 | -0.49 | -0.28 | -0.49 | -0.49 |
| dribbling | -0.014 | 0.05 | 0.018 | 0.35 | 0.34 | 0.81 | 0.78 | 0.4 | 0.79 | 0.78 | 1 | 0.81 | 0.71 | 0.57 | 0.9 | 0.7 | 0.67 | 0.7 | 0.38 | 0.55 | 0.74 | 0.0086 | 0.53 | -0.11 | 0.81 | 0.2 | 0.11 | 0.79 | 0.73 | 0.66 | 0.0041 | 0.067 | 0.046 | -0.65 | -0.65 | -0.43 | -0.65 | -0.66 |
| curve | -0.019 | -0.051 | -0.098 | 0.36 | 0.3 | 0.79 | 0.69 | 0.32 | 0.73 | 0.75 | 0.81 | 1 | 0.8 | 0.59 | 0.8 | 0.55 | 0.52 | 0.62 | 0.39 | 0.49 | 0.69 | -0.017 | 0.45 | -0.11 | 0.78 | 0.2 | 0.14 | 0.72 | 0.73 | 0.65 | 0.034 | 0.095 | 0.081 | -0.56 | -0.55 | -0.33 | -0.55 | -0.55 |
| free_kick_accuracy | -0.0076 | -0.11 | -0.15 | 0.35 | 0.26 | 0.71 | 0.63 | 0.31 | 0.69 | 0.68 | 0.71 | 0.8 | 1 | 0.6 | 0.72 | 0.43 | 0.39 | 0.5 | 0.37 | 0.43 | 0.68 | -0.033 | 0.42 | -0.056 | 0.77 | 0.23 | 0.18 | 0.65 | 0.7 | 0.67 | 0.075 | 0.13 | 0.11 | -0.5 | -0.49 | -0.27 | -0.49 | -0.5 |
| long_passing | -0.0074 | -0.11 | -0.14 | 0.44 | 0.34 | 0.68 | 0.34 | 0.36 | 0.8 | 0.41 | 0.57 | 0.59 | 0.6 | 1 | 0.67 | 0.32 | 0.3 | 0.38 | 0.4 | 0.38 | 0.54 | 0.045 | 0.53 | 0.067 | 0.57 | 0.46 | 0.54 | 0.48 | 0.67 | 0.48 | 0.44 | 0.49 | 0.46 | -0.46 | -0.46 | -0.25 | -0.46 | -0.46 |
| ball_control | -0.013 | -0.023 | -0.051 | 0.44 | 0.4 | 0.81 | 0.72 | 0.55 | 0.89 | 0.75 | 0.9 | 0.8 | 0.72 | 0.67 | 1 | 0.63 | 0.62 | 0.62 | 0.45 | 0.52 | 0.77 | 0.065 | 0.6 | 0.03 | 0.79 | 0.37 | 0.28 | 0.78 | 0.77 | 0.68 | 0.19 | 0.25 | 0.22 | -0.74 | -0.73 | -0.46 | -0.73 | -0.74 |
| acceleration | -0.0076 | 0.18 | 0.1 | 0.25 | 0.34 | 0.6 | 0.53 | 0.2 | 0.5 | 0.51 | 0.7 | 0.55 | 0.43 | 0.32 | 0.63 | 1 | 0.9 | 0.77 | 0.27 | 0.62 | 0.48 | 0.16 | 0.52 | -0.21 | 0.51 | 0.11 | 0.021 | 0.58 | 0.47 | 0.43 | -0.033 | -0.0049 | 0.0015 | -0.48 | -0.47 | -0.28 | -0.47 | -0.47 |
| sprint_speed | -0.011 | 0.18 | 0.096 | 0.25 | 0.34 | 0.58 | 0.51 | 0.27 | 0.49 | 0.49 | 0.67 | 0.52 | 0.39 | 0.3 | 0.62 | 0.9 | 1 | 0.7 | 0.27 | 0.54 | 0.49 | 0.18 | 0.55 | -0.11 | 0.49 | 0.15 | 0.053 | 0.57 | 0.44 | 0.41 | 0.0072 | 0.035 | 0.04 | -0.5 | -0.48 | -0.28 | -0.49 | -0.49 |
| agility | -0.00087 | 0.12 | 0.028 | 0.24 | 0.29 | 0.6 | 0.55 | 0.069 | 0.51 | 0.56 | 0.7 | 0.62 | 0.5 | 0.38 | 0.62 | 0.77 | 0.7 | 1 | 0.3 | 0.68 | 0.46 | 0.13 | 0.43 | -0.35 | 0.55 | 0.017 | -0.043 | 0.59 | 0.56 | 0.44 | -0.13 | -0.09 | -0.08 | -0.39 | -0.38 | -0.24 | -0.38 | -0.38 |
| reactions | -0.0042 | -0.23 | -0.31 | 0.77 | 0.58 | 0.38 | 0.35 | 0.3 | 0.46 | 0.4 | 0.38 | 0.39 | 0.37 | 0.4 | 0.45 | 0.27 | 0.27 | 0.3 | 1 | 0.21 | 0.42 | 0.24 | 0.36 | 0.24 | 0.41 | 0.33 | 0.24 | 0.41 | 0.45 | 0.39 | 0.12 | 0.16 | 0.14 | -0.075 | -0.082 | -0.037 | -0.081 | -0.081 |
| balance | -0.0094 | 0.0077 | 0.021 | 0.16 | 0.2 | 0.52 | 0.39 | 0.079 | 0.46 | 0.42 | 0.55 | 0.49 | 0.43 | 0.38 | 0.52 | 0.62 | 0.54 | 0.68 | 0.21 | 1 | 0.36 | 0.19 | 0.4 | -0.32 | 0.44 | 0.11 | 0.091 | 0.5 | 0.51 | 0.39 | 0.037 | 0.065 | 0.076 | -0.39 | -0.36 | -0.18 | -0.36 | -0.37 |
| shot_power | -0.0097 | -0.078 | -0.12 | 0.43 | 0.33 | 0.66 | 0.73 | 0.54 | 0.72 | 0.75 | 0.74 | 0.69 | 0.68 | 0.54 | 0.77 | 0.48 | 0.49 | 0.46 | 0.42 | 0.36 | 1 | 0.099 | 0.51 | 0.18 | 0.84 | 0.36 | 0.19 | 0.7 | 0.65 | 0.68 | 0.094 | 0.16 | 0.12 | -0.58 | -0.59 | -0.39 | -0.59 | -0.59 |
| jumping | -0.0042 | -0.073 | -0.14 | 0.26 | 0.17 | 0.021 | 0.009 | 0.29 | 0.06 | 0.023 | 0.0086 | -0.017 | -0.033 | 0.045 | 0.065 | 0.16 | 0.18 | 0.13 | 0.24 | 0.19 | 0.099 | 1 | 0.25 | 0.26 | 0.013 | 0.28 | 0.2 | 0.059 | 0.017 | 0.058 | 0.19 | 0.19 | 0.2 | -0.039 | -0.038 | -0.016 | -0.037 | -0.035 |
| stamina | -0.0098 | 0.012 | -0.11 | 0.33 | 0.26 | 0.56 | 0.35 | 0.48 | 0.61 | 0.38 | 0.53 | 0.45 | 0.42 | 0.53 | 0.6 | 0.52 | 0.55 | 0.43 | 0.36 | 0.4 | 0.51 | 0.25 | 1 | 0.24 | 0.48 | 0.54 | 0.48 | 0.5 | 0.51 | 0.4 | 0.42 | 0.46 | 0.44 | -0.55 | -0.54 | -0.31 | -0.54 | -0.55 |
| strength | -0.0083 | -0.18 | -0.23 | 0.32 | 0.13 | -0.07 | -0.053 | 0.49 | 0.092 | -0.036 | -0.11 | -0.11 | -0.056 | 0.067 | 0.03 | -0.21 | -0.11 | -0.35 | 0.24 | -0.32 | 0.18 | 0.26 | 0.24 | 1 | 0.0021 | 0.51 | 0.34 | -0.023 | -0.038 | 0.061 | 0.36 | 0.37 | 0.33 | -0.071 | -0.084 | -0.059 | -0.085 | -0.084 |
| long_shots | -0.01 | -0.067 | -0.12 | 0.39 | 0.31 | 0.72 | 0.81 | 0.41 | 0.73 | 0.81 | 0.81 | 0.78 | 0.77 | 0.57 | 0.79 | 0.51 | 0.49 | 0.55 | 0.41 | 0.44 | 0.84 | 0.013 | 0.48 | 0.0021 | 1 | 0.24 | 0.11 | 0.77 | 0.73 | 0.71 | -0.011 | 0.056 | 0.024 | -0.55 | -0.54 | -0.33 | -0.54 | -0.55 |
| aggression | -0.017 | -0.17 | -0.21 | 0.32 | 0.16 | 0.32 | 0.044 | 0.58 | 0.45 | 0.13 | 0.2 | 0.2 | 0.23 | 0.46 | 0.37 | 0.11 | 0.15 | 0.017 | 0.33 | 0.11 | 0.36 | 0.28 | 0.54 | 0.51 | 0.24 | 1 | 0.66 | 0.2 | 0.28 | 0.22 | 0.65 | 0.68 | 0.65 | -0.43 | -0.43 | -0.26 | -0.43 | -0.43 |
| interceptions | -0.0077 | -0.18 | -0.19 | 0.25 | 0.17 | 0.31 | -0.15 | 0.45 | 0.42 | -0.038 | 0.11 | 0.14 | 0.18 | 0.54 | 0.28 | 0.021 | 0.053 | -0.043 | 0.24 | 0.091 | 0.19 | 0.2 | 0.48 | 0.34 | 0.11 | 0.66 | 1 | 0.054 | 0.23 | 0.085 | 0.83 | 0.84 | 0.82 | -0.37 | -0.33 | -0.076 | -0.33 | -0.33 |
| positioning | -0.015 | -0.086 | -0.11 | 0.37 | 0.33 | 0.68 | 0.8 | 0.41 | 0.68 | 0.78 | 0.79 | 0.72 | 0.65 | 0.48 | 0.78 | 0.58 | 0.57 | 0.59 | 0.41 | 0.5 | 0.7 | 0.059 | 0.5 | -0.023 | 0.77 | 0.2 | 0.054 | 1 | 0.74 | 0.75 | -0.069 | -0.0096 | -0.041 | -0.55 | -0.5 | -0.22 | -0.51 | -0.51 |
| vision | -0.0077 | -0.16 | -0.19 | 0.43 | 0.38 | 0.69 | 0.65 | 0.34 | 0.77 | 0.69 | 0.73 | 0.73 | 0.7 | 0.67 | 0.77 | 0.47 | 0.44 | 0.56 | 0.45 | 0.51 | 0.65 | 0.017 | 0.51 | -0.038 | 0.73 | 0.28 | 0.23 | 0.74 | 1 | 0.67 | 0.081 | 0.15 | 0.12 | -0.5 | -0.46 | -0.2 | -0.46 | -0.47 |
| penalties | -0.011 | -0.18 | -0.16 | 0.39 | 0.32 | 0.57 | 0.72 | 0.43 | 0.61 | 0.71 | 0.66 | 0.65 | 0.67 | 0.48 | 0.68 | 0.43 | 0.41 | 0.44 | 0.39 | 0.39 | 0.68 | 0.058 | 0.4 | 0.061 | 0.71 | 0.22 | 0.085 | 0.75 | 0.67 | 1 | -0.038 | 0.0099 | -0.029 | -0.47 | -0.43 | -0.17 | -0.43 | -0.44 |
| marking | -0.0096 | -0.078 | -0.09 | 0.13 | 0.056 | 0.24 | -0.28 | 0.46 | 0.35 | -0.17 | 0.0041 | 0.034 | 0.075 | 0.44 | 0.19 | -0.033 | 0.0072 | -0.13 | 0.12 | 0.037 | 0.094 | 0.19 | 0.42 | 0.36 | -0.011 | 0.65 | 0.83 | -0.069 | 0.081 | -0.038 | 1 | 0.95 | 0.94 | -0.38 | -0.38 | -0.19 | -0.37 | -0.37 |
| standing_tackle | -0.012 | -0.073 | -0.087 | 0.17 | 0.084 | 0.29 | -0.23 | 0.48 | 0.42 | -0.11 | 0.067 | 0.095 | 0.13 | 0.49 | 0.25 | -0.0049 | 0.035 | -0.09 | 0.16 | 0.065 | 0.16 | 0.19 | 0.46 | 0.37 | 0.056 | 0.68 | 0.84 | -0.0096 | 0.15 | 0.0099 | 0.95 | 1 | 0.95 | -0.42 | -0.42 | -0.24 | -0.41 | -0.41 |
| sliding_tackle | -0.011 | -0.054 | -0.073 | 0.13 | 0.064 | 0.28 | -0.26 | 0.44 | 0.38 | -0.13 | 0.046 | 0.081 | 0.11 | 0.46 | 0.22 | 0.0015 | 0.04 | -0.08 | 0.14 | 0.076 | 0.12 | 0.2 | 0.44 | 0.33 | 0.024 | 0.65 | 0.82 | -0.041 | 0.12 | -0.029 | 0.94 | 0.95 | 1 | -0.4 | -0.39 | -0.21 | -0.39 | -0.39 |
| gk_diving | 0.014 | -0.092 | -0.071 | 0.028 | -0.011 | -0.6 | -0.48 | -0.67 | -0.69 | -0.51 | -0.65 | -0.56 | -0.5 | -0.46 | -0.74 | -0.48 | -0.5 | -0.39 | -0.075 | -0.39 | -0.58 | -0.039 | -0.55 | -0.071 | -0.55 | -0.43 | -0.37 | -0.55 | -0.5 | -0.47 | -0.38 | -0.42 | -0.4 | 1 | 0.93 | 0.57 | 0.93 | 0.94 |
| gk_handling | 0.01 | -0.14 | -0.13 | 0.0044 | 0.0047 | -0.6 | -0.47 | -0.65 | -0.69 | -0.49 | -0.65 | -0.55 | -0.49 | -0.46 | -0.73 | -0.47 | -0.48 | -0.38 | -0.082 | -0.36 | -0.59 | -0.038 | -0.54 | -0.084 | -0.54 | -0.43 | -0.33 | -0.5 | -0.46 | -0.43 | -0.38 | -0.42 | -0.39 | 0.93 | 1 | 0.74 | 0.97 | 0.97 |
| gk_kicking | 0.0086 | -0.27 | -0.24 | 0.026 | 0.089 | -0.35 | -0.29 | -0.39 | -0.41 | -0.28 | -0.43 | -0.33 | -0.27 | -0.25 | -0.46 | -0.28 | -0.28 | -0.24 | -0.037 | -0.18 | -0.39 | -0.016 | -0.31 | -0.059 | -0.33 | -0.26 | -0.076 | -0.22 | -0.2 | -0.17 | -0.19 | -0.24 | -0.21 | 0.57 | 0.74 | 1 | 0.74 | 0.73 |
| gk_positioning | 0.014 | -0.15 | -0.13 | 0.0057 | 0.0034 | -0.6 | -0.47 | -0.65 | -0.69 | -0.49 | -0.65 | -0.55 | -0.49 | -0.46 | -0.73 | -0.47 | -0.49 | -0.38 | -0.081 | -0.36 | -0.59 | -0.037 | -0.54 | -0.085 | -0.54 | -0.43 | -0.33 | -0.51 | -0.46 | -0.43 | -0.37 | -0.41 | -0.39 | 0.93 | 0.97 | 0.74 | 1 | 0.97 |
| gk_reflexes | 0.014 | -0.14 | -0.12 | 0.0057 | 0.004 | -0.6 | -0.47 | -0.65 | -0.69 | -0.49 | -0.66 | -0.55 | -0.5 | -0.46 | -0.74 | -0.47 | -0.49 | -0.38 | -0.081 | -0.37 | -0.59 | -0.035 | -0.55 | -0.084 | -0.55 | -0.43 | -0.33 | -0.51 | -0.47 | -0.44 | -0.37 | -0.41 | -0.39 | 0.94 | 0.97 | 0.73 | 0.97 | 1 |
player_attributes NULLs:
id 0 player_fifa_api_id 0 player_api_id 0 date 0 overall_rating 836 potential 836 preferred_foot 836 attacking_work_rate 3230 defensive_work_rate 836 crossing 836 finishing 836 heading_accuracy 836 short_passing 836 volleys 2713 dribbling 836 curve 2713 free_kick_accuracy 836 long_passing 836 ball_control 836 acceleration 836 sprint_speed 836 agility 2713 reactions 836 balance 2713 shot_power 836 jumping 2713 stamina 836 strength 836 long_shots 836 aggression 836 interceptions 836 positioning 836 vision 2713 penalties 836 marking 836 standing_tackle 836 sliding_tackle 2713 gk_diving 836 gk_handling 836 gk_kicking 836 gk_positioning 836 gk_reflexes 836 dtype: int64
Found df player_attributes with nulls..... ================================================== teams ================================================== teams INFO: <class 'pandas.core.frame.DataFrame'> RangeIndex: 299 entries, 0 to 298 Data columns (total 5 columns): id 299 non-null int64 team_api_id 299 non-null int64 team_fifa_api_id 288 non-null float64 team_long_name 299 non-null object team_short_name 299 non-null object dtypes: float64(1), int64(2), object(2) memory usage: 11.8+ KB
None
teams Describtion:
| count | mean | std | min | 25% | 50% | 75% | max | |
|---|---|---|---|---|---|---|---|---|
| id | 299.0 | 23735.301003 | 15167.914719 | 1.0 | 9552.50 | 22805.0 | 36250.50 | 51606.0 |
| team_api_id | 299.0 | 12340.521739 | 25940.411135 | 1601.0 | 8349.00 | 8655.0 | 9886.50 | 274581.0 |
| team_fifa_api_id | 288.0 | 21534.305556 | 42456.439408 | 1.0 | 178.75 | 673.5 | 1910.75 | 112513.0 |
teams Correlations:
| id | team_api_id | team_fifa_api_id | |
|---|---|---|---|
| id | 1 | -0.0016 | 0.036 |
| team_api_id | -0.0016 | 1 | 0.22 |
| team_fifa_api_id | 0.036 | 0.22 | 1 |
teams NULLs:
id 0 team_api_id 0 team_fifa_api_id 11 team_long_name 0 team_short_name 0 dtype: int64
Found df teams with nulls..... ================================================== team_attributes ================================================== team_attributes INFO: <class 'pandas.core.frame.DataFrame'> RangeIndex: 1458 entries, 0 to 1457 Data columns (total 25 columns): id 1458 non-null int64 team_fifa_api_id 1458 non-null int64 team_api_id 1458 non-null int64 date 1458 non-null object buildUpPlaySpeed 1458 non-null int64 buildUpPlaySpeedClass 1458 non-null object buildUpPlayDribbling 489 non-null float64 buildUpPlayDribblingClass 1458 non-null object buildUpPlayPassing 1458 non-null int64 buildUpPlayPassingClass 1458 non-null object buildUpPlayPositioningClass 1458 non-null object chanceCreationPassing 1458 non-null int64 chanceCreationPassingClass 1458 non-null object chanceCreationCrossing 1458 non-null int64 chanceCreationCrossingClass 1458 non-null object chanceCreationShooting 1458 non-null int64 chanceCreationShootingClass 1458 non-null object chanceCreationPositioningClass 1458 non-null object defencePressure 1458 non-null int64 defencePressureClass 1458 non-null object defenceAggression 1458 non-null int64 defenceAggressionClass 1458 non-null object defenceTeamWidth 1458 non-null int64 defenceTeamWidthClass 1458 non-null object defenceDefenderLineClass 1458 non-null object dtypes: float64(1), int64(11), object(13) memory usage: 284.9+ KB
None
team_attributes Describtion:
| count | mean | std | min | 25% | 50% | 75% | max | |
|---|---|---|---|---|---|---|---|---|
| id | 1458.0 | 729.500000 | 421.032659 | 1.0 | 365.25 | 729.5 | 1093.75 | 1458.0 |
| team_fifa_api_id | 1458.0 | 17706.982167 | 39179.857739 | 1.0 | 110.00 | 485.0 | 1900.00 | 112513.0 |
| team_api_id | 1458.0 | 9995.727023 | 13264.869900 | 1601.0 | 8457.75 | 8674.0 | 9904.00 | 274581.0 |
| buildUpPlaySpeed | 1458.0 | 52.462277 | 11.545869 | 20.0 | 45.00 | 52.0 | 62.00 | 80.0 |
| buildUpPlayDribbling | 489.0 | 48.607362 | 9.678290 | 24.0 | 42.00 | 49.0 | 55.00 | 77.0 |
| buildUpPlayPassing | 1458.0 | 48.490398 | 10.896101 | 20.0 | 40.00 | 50.0 | 55.00 | 80.0 |
| chanceCreationPassing | 1458.0 | 52.165295 | 10.360793 | 21.0 | 46.00 | 52.0 | 59.00 | 80.0 |
| chanceCreationCrossing | 1458.0 | 53.731824 | 11.086796 | 20.0 | 47.00 | 53.0 | 62.00 | 80.0 |
| chanceCreationShooting | 1458.0 | 53.969136 | 10.327566 | 22.0 | 48.00 | 53.0 | 61.00 | 80.0 |
| defencePressure | 1458.0 | 46.017147 | 10.227225 | 23.0 | 39.00 | 45.0 | 51.00 | 72.0 |
| defenceAggression | 1458.0 | 49.251029 | 9.738028 | 24.0 | 44.00 | 48.0 | 55.00 | 72.0 |
| defenceTeamWidth | 1458.0 | 52.185871 | 9.574712 | 29.0 | 47.00 | 52.0 | 58.00 | 73.0 |
team_attributes Correlations:
| id | team_fifa_api_id | team_api_id | buildUpPlaySpeed | buildUpPlayDribbling | buildUpPlayPassing | chanceCreationPassing | chanceCreationCrossing | chanceCreationShooting | defencePressure | defenceAggression | defenceTeamWidth | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| id | 1 | -0.01 | -0.09 | -0.029 | 0.049 | -0.019 | 0.018 | 0.02 | -0.02 | -0.013 | -0.052 | -0.048 |
| team_fifa_api_id | -0.01 | 1 | 0.16 | -0.017 | 0.11 | 0.0077 | -0.026 | -0.11 | 0.003 | -0.06 | 0.00052 | -0.072 |
| team_api_id | -0.09 | 0.16 | 1 | 0.0043 | 0.039 | 0.0014 | -0.0052 | -0.066 | -0.073 | -0.065 | -0.031 | -0.071 |
| buildUpPlaySpeed | -0.029 | -0.017 | 0.0043 | 1 | 0.068 | 0.4 | 0.32 | 0.19 | 0.072 | 0.046 | 0.16 | 0.067 |
| buildUpPlayDribbling | 0.049 | 0.11 | 0.039 | 0.068 | 1 | -0.12 | 0.08 | 0.056 | 0.12 | -0.018 | -0.036 | 0.086 |
| buildUpPlayPassing | -0.019 | 0.0077 | 0.0014 | 0.4 | -0.12 | 1 | 0.22 | 0.23 | -0.077 | -0.05 | 0.12 | 0.063 |
| chanceCreationPassing | 0.018 | -0.026 | -0.0052 | 0.32 | 0.08 | 0.22 | 1 | 0.25 | 0.11 | 0.2 | 0.15 | 0.15 |
| chanceCreationCrossing | 0.02 | -0.11 | -0.066 | 0.19 | 0.056 | 0.23 | 0.25 | 1 | -0.013 | 0.087 | 0.099 | 0.13 |
| chanceCreationShooting | -0.02 | 0.003 | -0.073 | 0.072 | 0.12 | -0.077 | 0.11 | -0.013 | 1 | 0.19 | 0.12 | 0.13 |
| defencePressure | -0.013 | -0.06 | -0.065 | 0.046 | -0.018 | -0.05 | 0.2 | 0.087 | 0.19 | 1 | 0.42 | 0.51 |
| defenceAggression | -0.052 | 0.00052 | -0.031 | 0.16 | -0.036 | 0.12 | 0.15 | 0.099 | 0.12 | 0.42 | 1 | 0.24 |
| defenceTeamWidth | -0.048 | -0.072 | -0.071 | 0.067 | 0.086 | 0.063 | 0.15 | 0.13 | 0.13 | 0.51 | 0.24 | 1 |
team_attributes NULLs:
id 0 team_fifa_api_id 0 team_api_id 0 date 0 buildUpPlaySpeed 0 buildUpPlaySpeedClass 0 buildUpPlayDribbling 969 buildUpPlayDribblingClass 0 buildUpPlayPassing 0 buildUpPlayPassingClass 0 buildUpPlayPositioningClass 0 chanceCreationPassing 0 chanceCreationPassingClass 0 chanceCreationCrossing 0 chanceCreationCrossingClass 0 chanceCreationShooting 0 chanceCreationShootingClass 0 chanceCreationPositioningClass 0 defencePressure 0 defencePressureClass 0 defenceAggression 0 defenceAggressionClass 0 defenceTeamWidth 0 defenceTeamWidthClass 0 defenceDefenderLineClass 0 dtype: int64
Found df team_attributes with nulls..... ================================================== sqlite_sequences ================================================== sqlite_sequences INFO: <class 'pandas.core.frame.DataFrame'> RangeIndex: 7 entries, 0 to 6 Data columns (total 2 columns): name 7 non-null object seq 7 non-null int64 dtypes: int64(1), object(1) memory usage: 240.0+ bytes
None
sqlite_sequences Describtion:
| count | mean | std | min | 25% | 50% | 75% | max | |
|---|---|---|---|---|---|---|---|---|
| seq | 7.0 | 65185.857143 | 62082.942398 | 1458.0 | 31516.5 | 51958.0 | 77937.0 | 183978.0 |
sqlite_sequences Correlations:
| seq | |
|---|---|
| seq | 1 |
sqlite_sequences NULLs:
name 0 seq 0 dtype: int64
dfs_with_nulls.keys()
dict_keys(['matches', 'player_attributes', 'teams', 'team_attributes'])
df = db.dfs['matches'].copy()
df.head(3)
| id | country_id | league_id | season | stage | date | match_api_id | home_team_api_id | away_team_api_id | home_team_goal | ... | SJA | VCH | VCD | VCA | GBH | GBD | GBA | BSH | BSD | BSA | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 1 | 1 | 1 | 2008/2009 | 1 | 2008-08-17 00:00:00 | 492473 | 9987 | 9993 | 1 | ... | 4.0 | 1.65 | 3.40 | 4.50 | 1.78 | 3.25 | 4.00 | 1.73 | 3.40 | 4.20 |
| 1 | 2 | 1 | 1 | 2008/2009 | 1 | 2008-08-16 00:00:00 | 492474 | 10000 | 9994 | 0 | ... | 3.8 | 2.00 | 3.25 | 3.25 | 1.85 | 3.25 | 3.75 | 1.91 | 3.25 | 3.60 |
| 2 | 3 | 1 | 1 | 2008/2009 | 1 | 2008-08-16 00:00:00 | 492475 | 9984 | 8635 | 0 | ... | 2.5 | 2.35 | 3.25 | 2.65 | 2.50 | 3.20 | 2.50 | 2.30 | 3.20 | 2.75 |
3 rows × 115 columns
df['league_id'].nunique()
11
df.isnull().sum()
id 0
country_id 0
league_id 0
season 0
stage 0
...
GBD 11817
GBA 11817
BSH 11818
BSD 11818
BSA 11818
Length: 115, dtype: int64
# How many total missing values do we have?
total_cells = np.product(df.shape)
total_missing = df.isnull().sum().sum()
# percent of data that is missing
percentage = (total_missing / total_cells) * 100
print(percentage)
13.63626474225838
df.dropna()['league_id'].nunique()
5
df = df.fillna(df.mean())
db.dfs['matches'] = df
df = db.dfs['player_attributes'].copy()
df.head(3)
| id | player_fifa_api_id | player_api_id | date | overall_rating | potential | preferred_foot | attacking_work_rate | defensive_work_rate | crossing | ... | vision | penalties | marking | standing_tackle | sliding_tackle | gk_diving | gk_handling | gk_kicking | gk_positioning | gk_reflexes | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 1 | 218353 | 505942 | 2016-02-18 00:00:00 | 67.0 | 71.0 | right | medium | medium | 49.0 | ... | 54.0 | 48.0 | 65.0 | 69.0 | 69.0 | 6.0 | 11.0 | 10.0 | 8.0 | 8.0 |
| 1 | 2 | 218353 | 505942 | 2015-11-19 00:00:00 | 67.0 | 71.0 | right | medium | medium | 49.0 | ... | 54.0 | 48.0 | 65.0 | 69.0 | 69.0 | 6.0 | 11.0 | 10.0 | 8.0 | 8.0 |
| 2 | 3 | 218353 | 505942 | 2015-09-21 00:00:00 | 62.0 | 66.0 | right | medium | medium | 49.0 | ... | 54.0 | 48.0 | 65.0 | 66.0 | 69.0 | 6.0 | 11.0 | 10.0 | 8.0 | 8.0 |
3 rows × 42 columns
df.isnull().sum()
id 0 player_fifa_api_id 0 player_api_id 0 date 0 overall_rating 836 potential 836 preferred_foot 836 attacking_work_rate 3230 defensive_work_rate 836 crossing 836 finishing 836 heading_accuracy 836 short_passing 836 volleys 2713 dribbling 836 curve 2713 free_kick_accuracy 836 long_passing 836 ball_control 836 acceleration 836 sprint_speed 836 agility 2713 reactions 836 balance 2713 shot_power 836 jumping 2713 stamina 836 strength 836 long_shots 836 aggression 836 interceptions 836 positioning 836 vision 2713 penalties 836 marking 836 standing_tackle 836 sliding_tackle 2713 gk_diving 836 gk_handling 836 gk_kicking 836 gk_positioning 836 gk_reflexes 836 dtype: int64
# How many total missing values do we have?
total_cells = np.product(df.shape)
total_missing = df.isnull().sum().sum()
# percent of data that is missing
percentage = (total_missing / total_cells) * 100
print(percentage)
0.6121461727566805
df.dropna()
| id | player_fifa_api_id | player_api_id | date | overall_rating | potential | preferred_foot | attacking_work_rate | defensive_work_rate | crossing | ... | vision | penalties | marking | standing_tackle | sliding_tackle | gk_diving | gk_handling | gk_kicking | gk_positioning | gk_reflexes | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 1 | 218353 | 505942 | 2016-02-18 00:00:00 | 67.0 | 71.0 | right | medium | medium | 49.0 | ... | 54.0 | 48.0 | 65.0 | 69.0 | 69.0 | 6.0 | 11.0 | 10.0 | 8.0 | 8.0 |
| 1 | 2 | 218353 | 505942 | 2015-11-19 00:00:00 | 67.0 | 71.0 | right | medium | medium | 49.0 | ... | 54.0 | 48.0 | 65.0 | 69.0 | 69.0 | 6.0 | 11.0 | 10.0 | 8.0 | 8.0 |
| 2 | 3 | 218353 | 505942 | 2015-09-21 00:00:00 | 62.0 | 66.0 | right | medium | medium | 49.0 | ... | 54.0 | 48.0 | 65.0 | 66.0 | 69.0 | 6.0 | 11.0 | 10.0 | 8.0 | 8.0 |
| 3 | 4 | 218353 | 505942 | 2015-03-20 00:00:00 | 61.0 | 65.0 | right | medium | medium | 48.0 | ... | 53.0 | 47.0 | 62.0 | 63.0 | 66.0 | 5.0 | 10.0 | 9.0 | 7.0 | 7.0 |
| 4 | 5 | 218353 | 505942 | 2007-02-22 00:00:00 | 61.0 | 65.0 | right | medium | medium | 48.0 | ... | 53.0 | 47.0 | 62.0 | 63.0 | 66.0 | 5.0 | 10.0 | 9.0 | 7.0 | 7.0 |
| ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... |
| 183973 | 183974 | 102359 | 39902 | 2009-08-30 00:00:00 | 83.0 | 85.0 | right | medium | low | 84.0 | ... | 88.0 | 83.0 | 22.0 | 31.0 | 30.0 | 9.0 | 20.0 | 84.0 | 20.0 | 20.0 |
| 183974 | 183975 | 102359 | 39902 | 2009-02-22 00:00:00 | 78.0 | 80.0 | right | medium | low | 74.0 | ... | 88.0 | 70.0 | 32.0 | 31.0 | 30.0 | 9.0 | 20.0 | 73.0 | 20.0 | 20.0 |
| 183975 | 183976 | 102359 | 39902 | 2008-08-30 00:00:00 | 77.0 | 80.0 | right | medium | low | 74.0 | ... | 88.0 | 70.0 | 32.0 | 31.0 | 30.0 | 9.0 | 20.0 | 73.0 | 20.0 | 20.0 |
| 183976 | 183977 | 102359 | 39902 | 2007-08-30 00:00:00 | 78.0 | 81.0 | right | medium | low | 74.0 | ... | 88.0 | 53.0 | 28.0 | 32.0 | 30.0 | 9.0 | 20.0 | 73.0 | 20.0 | 20.0 |
| 183977 | 183978 | 102359 | 39902 | 2007-02-22 00:00:00 | 80.0 | 81.0 | right | medium | low | 74.0 | ... | 88.0 | 53.0 | 38.0 | 32.0 | 30.0 | 9.0 | 9.0 | 78.0 | 7.0 | 15.0 |
180354 rows × 42 columns
len(df), len(df.dropna()), 'Difference =>', len(df) - len(df.dropna())
(183978, 180354, 'Difference =>', 3624)
df = df.fillna(method='bfill', axis=0).fillna(0)
db.dfs['player_attributes'] = df
df = db.dfs['teams'].copy()
df.head(3)
| id | team_api_id | team_fifa_api_id | team_long_name | team_short_name | |
|---|---|---|---|---|---|
| 0 | 1 | 9987 | 673.0 | KRC Genk | GEN |
| 1 | 2 | 9993 | 675.0 | Beerschot AC | BAC |
| 2 | 3 | 10000 | 15005.0 | SV Zulte-Waregem | ZUL |
df.isnull().sum()
id 0 team_api_id 0 team_fifa_api_id 11 team_long_name 0 team_short_name 0 dtype: int64
# How many total missing values do we have?
total_cells = np.product(df.shape)
total_missing = df.isnull().sum().sum()
# percent of data that is missing
percentage = (total_missing / total_cells) * 100
print(percentage)
0.7357859531772575
df[df.isnull().any(axis=1)]
| id | team_api_id | team_fifa_api_id | team_long_name | team_short_name | |
|---|---|---|---|---|---|
| 8 | 9 | 7947 | NaN | FCV Dender EH | DEN |
| 14 | 15 | 4049 | NaN | Tubize | TUB |
| 170 | 26561 | 6601 | NaN | FC Volendam | VOL |
| 204 | 34816 | 177361 | NaN | Termalica Bruk-Bet Nieciecza | TBN |
| 208 | 35286 | 7992 | NaN | Trofense | TRO |
| 213 | 35291 | 10213 | NaN | Amadora | AMA |
| 223 | 36248 | 9765 | NaN | Portimonense | POR |
| 225 | 36723 | 4064 | NaN | Feirense | FEI |
| 232 | 38789 | 6367 | NaN | Uniao da Madeira | MAD |
| 233 | 38791 | 188163 | NaN | Tondela | TON |
| 298 | 51606 | 7896 | NaN | Lugano | LUG |
df = df.drop(columns=['team_fifa_api_id'])
db.dfs['teams'] = df
df = db.dfs['team_attributes'].copy()
df.head(3)
| id | team_fifa_api_id | team_api_id | date | buildUpPlaySpeed | buildUpPlaySpeedClass | buildUpPlayDribbling | buildUpPlayDribblingClass | buildUpPlayPassing | buildUpPlayPassingClass | ... | chanceCreationShooting | chanceCreationShootingClass | chanceCreationPositioningClass | defencePressure | defencePressureClass | defenceAggression | defenceAggressionClass | defenceTeamWidth | defenceTeamWidthClass | defenceDefenderLineClass | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 1 | 434 | 9930 | 2010-02-22 00:00:00 | 60 | Balanced | NaN | Little | 50 | Mixed | ... | 55 | Normal | Organised | 50 | Medium | 55 | Press | 45 | Normal | Cover |
| 1 | 2 | 434 | 9930 | 2014-09-19 00:00:00 | 52 | Balanced | 48.0 | Normal | 56 | Mixed | ... | 64 | Normal | Organised | 47 | Medium | 44 | Press | 54 | Normal | Cover |
| 2 | 3 | 434 | 9930 | 2015-09-10 00:00:00 | 47 | Balanced | 41.0 | Normal | 54 | Mixed | ... | 64 | Normal | Organised | 47 | Medium | 44 | Press | 54 | Normal | Cover |
3 rows × 25 columns
df.isnull().sum()
id 0 team_fifa_api_id 0 team_api_id 0 date 0 buildUpPlaySpeed 0 buildUpPlaySpeedClass 0 buildUpPlayDribbling 969 buildUpPlayDribblingClass 0 buildUpPlayPassing 0 buildUpPlayPassingClass 0 buildUpPlayPositioningClass 0 chanceCreationPassing 0 chanceCreationPassingClass 0 chanceCreationCrossing 0 chanceCreationCrossingClass 0 chanceCreationShooting 0 chanceCreationShootingClass 0 chanceCreationPositioningClass 0 defencePressure 0 defencePressureClass 0 defenceAggression 0 defenceAggressionClass 0 defenceTeamWidth 0 defenceTeamWidthClass 0 defenceDefenderLineClass 0 dtype: int64
# How many total missing values do we have?
total_cells = np.product(df.shape)
total_missing = df.isnull().sum().sum()
# percent of data that is missing
percentage = (total_missing / total_cells) * 100
print(percentage)
2.6584362139917697
df[df.isnull().any(axis=1)]
| id | team_fifa_api_id | team_api_id | date | buildUpPlaySpeed | buildUpPlaySpeedClass | buildUpPlayDribbling | buildUpPlayDribblingClass | buildUpPlayPassing | buildUpPlayPassingClass | ... | chanceCreationShooting | chanceCreationShootingClass | chanceCreationPositioningClass | defencePressure | defencePressureClass | defenceAggression | defenceAggressionClass | defenceTeamWidth | defenceTeamWidthClass | defenceDefenderLineClass | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 1 | 434 | 9930 | 2010-02-22 00:00:00 | 60 | Balanced | NaN | Little | 50 | Mixed | ... | 55 | Normal | Organised | 50 | Medium | 55 | Press | 45 | Normal | Cover |
| 3 | 4 | 77 | 8485 | 2010-02-22 00:00:00 | 70 | Fast | NaN | Little | 70 | Long | ... | 70 | Lots | Organised | 60 | Medium | 70 | Double | 70 | Wide | Cover |
| 4 | 5 | 77 | 8485 | 2011-02-22 00:00:00 | 47 | Balanced | NaN | Little | 52 | Mixed | ... | 52 | Normal | Organised | 47 | Medium | 47 | Press | 52 | Normal | Cover |
| 5 | 6 | 77 | 8485 | 2012-02-22 00:00:00 | 58 | Balanced | NaN | Little | 62 | Mixed | ... | 55 | Normal | Organised | 40 | Medium | 40 | Press | 60 | Normal | Cover |
| 6 | 7 | 77 | 8485 | 2013-09-20 00:00:00 | 62 | Balanced | NaN | Little | 45 | Mixed | ... | 55 | Normal | Organised | 42 | Medium | 42 | Press | 60 | Normal | Cover |
| ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... |
| 1447 | 1448 | 244 | 8394 | 2013-09-20 00:00:00 | 38 | Balanced | NaN | Little | 23 | Short | ... | 57 | Normal | Organised | 51 | Medium | 46 | Press | 61 | Normal | Cover |
| 1452 | 1453 | 15005 | 10000 | 2010-02-22 00:00:00 | 65 | Balanced | NaN | Little | 60 | Mixed | ... | 50 | Normal | Organised | 70 | High | 60 | Press | 70 | Wide | Cover |
| 1453 | 1454 | 15005 | 10000 | 2011-02-22 00:00:00 | 52 | Balanced | NaN | Little | 52 | Mixed | ... | 53 | Normal | Organised | 46 | Medium | 48 | Press | 53 | Normal | Cover |
| 1454 | 1455 | 15005 | 10000 | 2012-02-22 00:00:00 | 54 | Balanced | NaN | Little | 51 | Mixed | ... | 50 | Normal | Organised | 44 | Medium | 55 | Press | 53 | Normal | Cover |
| 1455 | 1456 | 15005 | 10000 | 2013-09-20 00:00:00 | 54 | Balanced | NaN | Little | 51 | Mixed | ... | 32 | Little | Organised | 44 | Medium | 58 | Press | 37 | Normal | Cover |
969 rows × 25 columns
df = df.drop(columns=['buildUpPlayDribbling'])
db.dfs['team_attributes'] = df
display_tables(db.dfs)
'countries'
|
'leagues'
|
'matches'
25979 rows × 115 columns |
'players'
11060 rows × 7 columns |
'player_attributes'
183978 rows × 42 columns |
'teams'
299 rows × 4 columns |
'team_attributes'
1458 rows × 24 columns |
'sqlite_sequences'
|
df = db.dfs['players'].copy()
df.head(3)
| id | player_api_id | player_name | player_fifa_api_id | birthday | height | weight | |
|---|---|---|---|---|---|---|---|
| 0 | 1 | 505942 | Aaron Appindangoye | 218353 | 1992-02-29 00:00:00 | 182.88 | 187 |
| 1 | 2 | 155782 | Aaron Cresswell | 189615 | 1989-12-15 00:00:00 | 170.18 | 146 |
| 2 | 3 | 162549 | Aaron Doran | 186170 | 1991-05-13 00:00:00 | 170.18 | 163 |
df['birthday'] = pd.to_datetime(df['birthday'])
df.head(3)
| id | player_api_id | player_name | player_fifa_api_id | birthday | height | weight | |
|---|---|---|---|---|---|---|---|
| 0 | 1 | 505942 | Aaron Appindangoye | 218353 | 1992-02-29 | 182.88 | 187 |
| 1 | 2 | 155782 | Aaron Cresswell | 189615 | 1989-12-15 | 170.18 | 146 |
| 2 | 3 | 162549 | Aaron Doran | 186170 | 1991-05-13 | 170.18 | 163 |
now = pd.Timestamp('now')
df['age'] = (now - df['birthday']).astype('<m8[Y]').apply(int)
df.head(3)
| id | player_api_id | player_name | player_fifa_api_id | birthday | height | weight | age | |
|---|---|---|---|---|---|---|---|---|
| 0 | 1 | 505942 | Aaron Appindangoye | 218353 | 1992-02-29 | 182.88 | 187 | 27 |
| 1 | 2 | 155782 | Aaron Cresswell | 189615 | 1989-12-15 | 170.18 | 146 | 29 |
| 2 | 3 | 162549 | Aaron Doran | 186170 | 1991-05-13 | 170.18 | 163 | 28 |
db.dfs['players'] = df
df = db.dfs['player_attributes'].copy()
df.head(3)
| id | player_fifa_api_id | player_api_id | date | overall_rating | potential | preferred_foot | attacking_work_rate | defensive_work_rate | crossing | ... | vision | penalties | marking | standing_tackle | sliding_tackle | gk_diving | gk_handling | gk_kicking | gk_positioning | gk_reflexes | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 1 | 218353 | 505942 | 2016-02-18 00:00:00 | 67.0 | 71.0 | right | medium | medium | 49.0 | ... | 54.0 | 48.0 | 65.0 | 69.0 | 69.0 | 6.0 | 11.0 | 10.0 | 8.0 | 8.0 |
| 1 | 2 | 218353 | 505942 | 2015-11-19 00:00:00 | 67.0 | 71.0 | right | medium | medium | 49.0 | ... | 54.0 | 48.0 | 65.0 | 69.0 | 69.0 | 6.0 | 11.0 | 10.0 | 8.0 | 8.0 |
| 2 | 3 | 218353 | 505942 | 2015-09-21 00:00:00 | 62.0 | 66.0 | right | medium | medium | 49.0 | ... | 54.0 | 48.0 | 65.0 | 66.0 | 69.0 | 6.0 | 11.0 | 10.0 | 8.0 | 8.0 |
3 rows × 42 columns
players_and_attr = (db.dfs['players']
.merge(df, on="player_api_id", how='outer')
.rename(columns={'player_fifa_api_id_x':"player_fifa_api_id"}))
players_and_attr = players_and_attr.drop(["id_x", "id_y", "player_fifa_api_id_y"], axis = 1)
df = db.dfs['players_and_attr'] = players_and_attr
df
| player_api_id | player_name | player_fifa_api_id | birthday | height | weight | age | date | overall_rating | potential | ... | vision | penalties | marking | standing_tackle | sliding_tackle | gk_diving | gk_handling | gk_kicking | gk_positioning | gk_reflexes | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 505942 | Aaron Appindangoye | 218353 | 1992-02-29 | 182.88 | 187 | 27 | 2016-02-18 00:00:00 | 67.0 | 71.0 | ... | 54.0 | 48.0 | 65.0 | 69.0 | 69.0 | 6.0 | 11.0 | 10.0 | 8.0 | 8.0 |
| 1 | 505942 | Aaron Appindangoye | 218353 | 1992-02-29 | 182.88 | 187 | 27 | 2015-11-19 00:00:00 | 67.0 | 71.0 | ... | 54.0 | 48.0 | 65.0 | 69.0 | 69.0 | 6.0 | 11.0 | 10.0 | 8.0 | 8.0 |
| 2 | 505942 | Aaron Appindangoye | 218353 | 1992-02-29 | 182.88 | 187 | 27 | 2015-09-21 00:00:00 | 62.0 | 66.0 | ... | 54.0 | 48.0 | 65.0 | 66.0 | 69.0 | 6.0 | 11.0 | 10.0 | 8.0 | 8.0 |
| 3 | 505942 | Aaron Appindangoye | 218353 | 1992-02-29 | 182.88 | 187 | 27 | 2015-03-20 00:00:00 | 61.0 | 65.0 | ... | 53.0 | 47.0 | 62.0 | 63.0 | 66.0 | 5.0 | 10.0 | 9.0 | 7.0 | 7.0 |
| 4 | 505942 | Aaron Appindangoye | 218353 | 1992-02-29 | 182.88 | 187 | 27 | 2007-02-22 00:00:00 | 61.0 | 65.0 | ... | 53.0 | 47.0 | 62.0 | 63.0 | 66.0 | 5.0 | 10.0 | 9.0 | 7.0 | 7.0 |
| ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... |
| 183973 | 39902 | Zvjezdan Misimovic | 102359 | 1982-06-05 | 180.34 | 176 | 37 | 2009-08-30 00:00:00 | 83.0 | 85.0 | ... | 88.0 | 83.0 | 22.0 | 31.0 | 30.0 | 9.0 | 20.0 | 84.0 | 20.0 | 20.0 |
| 183974 | 39902 | Zvjezdan Misimovic | 102359 | 1982-06-05 | 180.34 | 176 | 37 | 2009-02-22 00:00:00 | 78.0 | 80.0 | ... | 88.0 | 70.0 | 32.0 | 31.0 | 30.0 | 9.0 | 20.0 | 73.0 | 20.0 | 20.0 |
| 183975 | 39902 | Zvjezdan Misimovic | 102359 | 1982-06-05 | 180.34 | 176 | 37 | 2008-08-30 00:00:00 | 77.0 | 80.0 | ... | 88.0 | 70.0 | 32.0 | 31.0 | 30.0 | 9.0 | 20.0 | 73.0 | 20.0 | 20.0 |
| 183976 | 39902 | Zvjezdan Misimovic | 102359 | 1982-06-05 | 180.34 | 176 | 37 | 2007-08-30 00:00:00 | 78.0 | 81.0 | ... | 88.0 | 53.0 | 28.0 | 32.0 | 30.0 | 9.0 | 20.0 | 73.0 | 20.0 | 20.0 |
| 183977 | 39902 | Zvjezdan Misimovic | 102359 | 1982-06-05 | 180.34 | 176 | 37 | 2007-02-22 00:00:00 | 80.0 | 81.0 | ... | 88.0 | 53.0 | 38.0 | 32.0 | 30.0 | 9.0 | 9.0 | 78.0 | 7.0 | 15.0 |
183978 rows × 46 columns
df.groupby('player_name').count()
| player_api_id | player_fifa_api_id | birthday | height | weight | age | date | overall_rating | potential | preferred_foot | ... | vision | penalties | marking | standing_tackle | sliding_tackle | gk_diving | gk_handling | gk_kicking | gk_positioning | gk_reflexes | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| player_name | |||||||||||||||||||||
| Aaron Appindangoye | 5 | 5 | 5 | 5 | 5 | 5 | 5 | 5 | 5 | 5 | ... | 5 | 5 | 5 | 5 | 5 | 5 | 5 | 5 | 5 | 5 |
| Aaron Cresswell | 33 | 33 | 33 | 33 | 33 | 33 | 33 | 33 | 33 | 33 | ... | 33 | 33 | 33 | 33 | 33 | 33 | 33 | 33 | 33 | 33 |
| Aaron Doran | 26 | 26 | 26 | 26 | 26 | 26 | 26 | 26 | 26 | 26 | ... | 26 | 26 | 26 | 26 | 26 | 26 | 26 | 26 | 26 | 26 |
| Aaron Galindo | 23 | 23 | 23 | 23 | 23 | 23 | 23 | 23 | 23 | 23 | ... | 23 | 23 | 23 | 23 | 23 | 23 | 23 | 23 | 23 | 23 |
| Aaron Hughes | 25 | 25 | 25 | 25 | 25 | 25 | 25 | 25 | 25 | 25 | ... | 25 | 25 | 25 | 25 | 25 | 25 | 25 | 25 | 25 | 25 |
| ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... |
| Zsolt Low | 7 | 7 | 7 | 7 | 7 | 7 | 7 | 7 | 7 | 7 | ... | 7 | 7 | 7 | 7 | 7 | 7 | 7 | 7 | 7 | 7 |
| Zurab Khizanishvili | 8 | 8 | 8 | 8 | 8 | 8 | 8 | 8 | 8 | 8 | ... | 8 | 8 | 8 | 8 | 8 | 8 | 8 | 8 | 8 | 8 |
| Zvjezdan Misimovic | 10 | 10 | 10 | 10 | 10 | 10 | 10 | 10 | 10 | 10 | ... | 10 | 10 | 10 | 10 | 10 | 10 | 10 | 10 | 10 | 10 |
| de Oliveira Cleber Monteiro | 9 | 9 | 9 | 9 | 9 | 9 | 9 | 9 | 9 | 9 | ... | 9 | 9 | 9 | 9 | 9 | 9 | 9 | 9 | 9 | 9 |
| dos Santos Fabio Junior | 4 | 4 | 4 | 4 | 4 | 4 | 4 | 4 | 4 | 4 | ... | 4 | 4 | 4 | 4 | 4 | 4 | 4 | 4 | 4 | 4 |
10848 rows × 45 columns
df.sort_values("date", inplace=True, ascending=False)
df
| player_api_id | player_name | player_fifa_api_id | birthday | height | weight | age | date | overall_rating | potential | ... | vision | penalties | marking | standing_tackle | sliding_tackle | gk_diving | gk_handling | gk_kicking | gk_positioning | gk_reflexes | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 95620 | 307224 | Kevin Koubemba | 208127 | 1993-03-23 | 193.04 | 198 | 26 | 2016-07-07 00:00:00 | 64.0 | 68.0 | ... | 55.0 | 65.0 | 22.0 | 22.0 | 25.0 | 12.0 | 12.0 | 7.0 | 11.0 | 12.0 |
| 57229 | 184521 | Florian Lejeune | 197948 | 1991-05-20 | 187.96 | 179 | 28 | 2016-07-07 00:00:00 | 73.0 | 77.0 | ... | 32.0 | 43.0 | 74.0 | 75.0 | 69.0 | 11.0 | 15.0 | 15.0 | 12.0 | 7.0 |
| 181048 | 512726 | Yanis Mbombo Lokwa | 221274 | 1994-04-08 | 177.80 | 172 | 25 | 2016-07-07 00:00:00 | 63.0 | 72.0 | ... | 48.0 | 59.0 | 15.0 | 16.0 | 12.0 | 11.0 | 12.0 | 12.0 | 12.0 | 7.0 |
| 178639 | 450002 | Wallace | 216437 | 1993-10-14 | 190.50 | 183 | 26 | 2016-07-07 00:00:00 | 74.0 | 82.0 | ... | 31.0 | 45.0 | 76.0 | 78.0 | 74.0 | 15.0 | 11.0 | 11.0 | 10.0 | 11.0 |
| 153508 | 45400 | Ronnie Schwartz | 172555 | 1989-08-29 | 182.88 | 176 | 30 | 2016-07-07 00:00:00 | 68.0 | 70.0 | ... | 45.0 | 66.0 | 23.0 | 17.0 | 23.0 | 13.0 | 11.0 | 6.0 | 9.0 | 14.0 |
| ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... |
| 115250 | 150119 | Marko Vejinovic | 189715 | 1990-02-03 | 185.42 | 152 | 29 | 2007-02-22 00:00:00 | 59.0 | 67.0 | ... | 71.0 | 56.0 | 54.0 | 57.0 | 41.0 | 7.0 | 22.0 | 64.0 | 22.0 | 22.0 |
| 115219 | 12473 | Marko Suler | 186689 | 1983-03-09 | 185.42 | 174 | 36 | 2007-02-22 00:00:00 | 64.0 | 69.0 | ... | 53.0 | 65.0 | 64.0 | 65.0 | 79.0 | 4.0 | 21.0 | 53.0 | 21.0 | 21.0 |
| 115203 | 213487 | Marko Scepovic | 220121 | 1991-05-23 | 190.50 | 183 | 28 | 2007-02-22 00:00:00 | 69.0 | 77.0 | ... | 64.0 | 57.0 | 30.0 | 31.0 | 38.0 | 7.0 | 12.0 | 6.0 | 7.0 | 13.0 |
| 115190 | 425988 | Marko Poletanovic | 227150 | 1993-07-20 | 187.96 | 159 | 26 | 2007-02-22 00:00:00 | 66.0 | 74.0 | ... | 67.0 | 54.0 | 53.0 | 62.0 | 61.0 | 14.0 | 13.0 | 14.0 | 10.0 | 12.0 |
| 183977 | 39902 | Zvjezdan Misimovic | 102359 | 1982-06-05 | 180.34 | 176 | 37 | 2007-02-22 00:00:00 | 80.0 | 81.0 | ... | 88.0 | 53.0 | 38.0 | 32.0 | 30.0 | 9.0 | 9.0 | 78.0 | 7.0 | 15.0 |
183978 rows × 46 columns
df.drop_duplicates(subset ="player_name",
keep = 'first', inplace = True)
df.groupby('player_name').count()
| player_api_id | player_fifa_api_id | birthday | height | weight | age | date | overall_rating | potential | preferred_foot | ... | vision | penalties | marking | standing_tackle | sliding_tackle | gk_diving | gk_handling | gk_kicking | gk_positioning | gk_reflexes | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| player_name | |||||||||||||||||||||
| Aaron Appindangoye | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | ... | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 |
| Aaron Cresswell | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | ... | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 |
| Aaron Doran | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | ... | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 |
| Aaron Galindo | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | ... | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 |
| Aaron Hughes | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | ... | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 |
| ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... |
| Zsolt Low | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | ... | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 |
| Zurab Khizanishvili | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | ... | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 |
| Zvjezdan Misimovic | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | ... | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 |
| de Oliveira Cleber Monteiro | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | ... | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 |
| dos Santos Fabio Junior | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | ... | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 |
10848 rows × 45 columns
players_in_2016 = df[df['date'].str.contains('2016')]
db.dfs['players_in_2016'] = players_in_2016
df1, df2 = db.dfs['countries'].copy(), db.dfs['leagues'].copy()
df = db.dfs['leagues_by_countries'] = (df1.merge(df2, left_on="id", right_on="id", how="outer")
.rename(columns={'name_x':"country", 'name_y':"league"}))
df = df.drop("id", axis = 1)
df
| country | country_id | league | |
|---|---|---|---|
| 0 | Belgium | 1 | Belgium Jupiler League |
| 1 | England | 1729 | England Premier League |
| 2 | France | 4769 | France Ligue 1 |
| 3 | Germany | 7809 | Germany 1. Bundesliga |
| 4 | Italy | 10257 | Italy Serie A |
| 5 | Netherlands | 13274 | Netherlands Eredivisie |
| 6 | Poland | 15722 | Poland Ekstraklasa |
| 7 | Portugal | 17642 | Portugal Liga ZON Sagres |
| 8 | Scotland | 19694 | Scotland Premier League |
| 9 | Spain | 21518 | Spain LIGA BBVA |
| 10 | Switzerland | 24558 | Switzerland Super League |
df = db.dfs['matches'].copy()
df.head(3)
| id | country_id | league_id | season | stage | date | match_api_id | home_team_api_id | away_team_api_id | home_team_goal | ... | SJA | VCH | VCD | VCA | GBH | GBD | GBA | BSH | BSD | BSA | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 1 | 1 | 1 | 2008/2009 | 1 | 2008-08-17 00:00:00 | 492473 | 9987 | 9993 | 1 | ... | 4.0 | 1.65 | 3.40 | 4.50 | 1.78 | 3.25 | 4.00 | 1.73 | 3.40 | 4.20 |
| 1 | 2 | 1 | 1 | 2008/2009 | 1 | 2008-08-16 00:00:00 | 492474 | 10000 | 9994 | 0 | ... | 3.8 | 2.00 | 3.25 | 3.25 | 1.85 | 3.25 | 3.75 | 1.91 | 3.25 | 3.60 |
| 2 | 3 | 1 | 1 | 2008/2009 | 1 | 2008-08-16 00:00:00 | 492475 | 9984 | 8635 | 0 | ... | 2.5 | 2.35 | 3.25 | 2.65 | 2.50 | 3.20 | 2.50 | 2.30 | 3.20 | 2.75 |
3 rows × 115 columns
list(df.columns)
['id', 'country_id', 'league_id', 'season', 'stage', 'date', 'match_api_id', 'home_team_api_id', 'away_team_api_id', 'home_team_goal', 'away_team_goal', 'home_player_X1', 'home_player_X2', 'home_player_X3', 'home_player_X4', 'home_player_X5', 'home_player_X6', 'home_player_X7', 'home_player_X8', 'home_player_X9', 'home_player_X10', 'home_player_X11', 'away_player_X1', 'away_player_X2', 'away_player_X3', 'away_player_X4', 'away_player_X5', 'away_player_X6', 'away_player_X7', 'away_player_X8', 'away_player_X9', 'away_player_X10', 'away_player_X11', 'home_player_Y1', 'home_player_Y2', 'home_player_Y3', 'home_player_Y4', 'home_player_Y5', 'home_player_Y6', 'home_player_Y7', 'home_player_Y8', 'home_player_Y9', 'home_player_Y10', 'home_player_Y11', 'away_player_Y1', 'away_player_Y2', 'away_player_Y3', 'away_player_Y4', 'away_player_Y5', 'away_player_Y6', 'away_player_Y7', 'away_player_Y8', 'away_player_Y9', 'away_player_Y10', 'away_player_Y11', 'home_player_1', 'home_player_2', 'home_player_3', 'home_player_4', 'home_player_5', 'home_player_6', 'home_player_7', 'home_player_8', 'home_player_9', 'home_player_10', 'home_player_11', 'away_player_1', 'away_player_2', 'away_player_3', 'away_player_4', 'away_player_5', 'away_player_6', 'away_player_7', 'away_player_8', 'away_player_9', 'away_player_10', 'away_player_11', 'goal', 'shoton', 'shotoff', 'foulcommit', 'card', 'cross', 'corner', 'possession', 'B365H', 'B365D', 'B365A', 'BWH', 'BWD', 'BWA', 'IWH', 'IWD', 'IWA', 'LBH', 'LBD', 'LBA', 'PSH', 'PSD', 'PSA', 'WHH', 'WHD', 'WHA', 'SJH', 'SJD', 'SJA', 'VCH', 'VCD', 'VCA', 'GBH', 'GBD', 'GBA', 'BSH', 'BSD', 'BSA']
list(df.columns)[:11]
['id', 'country_id', 'league_id', 'season', 'stage', 'date', 'match_api_id', 'home_team_api_id', 'away_team_api_id', 'home_team_goal', 'away_team_goal']
db.dfs['matches_with_less_attr'] = df[list(df.columns)[:11]].drop("id",axis=1)
db.dfs['matches_with_less_attr'].head(3)
| country_id | league_id | season | stage | date | match_api_id | home_team_api_id | away_team_api_id | home_team_goal | away_team_goal | |
|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 1 | 1 | 2008/2009 | 1 | 2008-08-17 00:00:00 | 492473 | 9987 | 9993 | 1 | 1 |
| 1 | 1 | 1 | 2008/2009 | 1 | 2008-08-16 00:00:00 | 492474 | 10000 | 9994 | 0 | 0 |
| 2 | 1 | 1 | 2008/2009 | 1 | 2008-08-16 00:00:00 | 492475 | 9984 | 8635 | 0 | 3 |
leagues_and_matches = db.dfs['matches_with_less_attr'].merge(db.dfs['leagues_by_countries'],
left_on="country_id",
right_on="country_id",
how="outer")
db.dfs['leagues_and_matches'] = leagues_and_matches
leagues_and_matches.head(3)
| country_id | league_id | season | stage | date | match_api_id | home_team_api_id | away_team_api_id | home_team_goal | away_team_goal | id | country | league | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 1 | 1 | 2008/2009 | 1 | 2008-08-17 00:00:00 | 492473 | 9987 | 9993 | 1 | 1 | 1 | Belgium | Belgium Jupiler League |
| 1 | 1 | 1 | 2008/2009 | 1 | 2008-08-16 00:00:00 | 492474 | 10000 | 9994 | 0 | 0 | 1 | Belgium | Belgium Jupiler League |
| 2 | 1 | 1 | 2008/2009 | 1 | 2008-08-16 00:00:00 | 492475 | 9984 | 8635 | 0 | 3 | 1 | Belgium | Belgium Jupiler League |
#getting lat lon info
leagues_by_countries = db.dfs['leagues_by_countries']
lat_long = db.lat_long
country_info = leagues_by_countries.merge(lat_long, left_on="country", right_on="name", how="left")
country_info = country_info.drop(["country_id","country_y","name"],axis = 1)
m3 = Basemap(projection='ortho', resolution=None, lat_0=50, lon_0=10,urcrnrlat=80,llcrnrlat=-80)
plt.figure(figsize=(15, 15))
country = list(country_info["country_x"].unique())
c = sns.color_palette("Set2",len(country))
label = country
def function(country,c,label):
lat = list(country_info[country_info["country_x"] == country].latitude)
lon = list(country_info[country_info["country_x"] == country].longitude)
x,y = m3(lon,lat)
m3.plot(x,y,"go",markersize=15,color=j,alpha=.8,label=i)
for i,j in zip(country,c):
function(i,j,i)
m3.bluemarble(scale=0.5)
plt.legend(loc="center right",frameon=True,prop={"size":15}).get_frame().set_facecolor("white")
plt.title("Countries & Matches")
plt.show()
Clipping input data to the valid range for imshow with RGB data ([0..1] for floats or [0..255] for integers).
db.dfs.keys()
dict_keys(['countries', 'leagues', 'matches', 'players', 'player_attributes', 'teams', 'team_attributes', 'sqlite_sequences', 'players_and_attr', 'players_in_2016', 'leagues_by_countries', 'matches_with_less_attr', 'leagues_and_matches'])
df = db.dfs['leagues_and_matches']
plt.figure(figsize=(8,8))
ax = sns.countplot(y = df["league"],
order=df["league"].value_counts().index,
linewidth = 1,
edgecolor = "k"*df["league"].nunique()
)
for i,j in enumerate(df["league"].value_counts().values):
ax.text(.7,i,j,weight = "bold")
plt.title("Matches by league")
plt.show()
df.groupby("league").agg({"home_team_goal":"sum","away_team_goal":"sum"}).plot(kind="barh",
figsize = (10,10),
edgecolor = "k",
linewidth =1
)
plt.title("Home and away goals by league")
plt.legend(loc = "best" , prop = {"size" : 14})
plt.xlabel("total goals")
plt.show()
db.dfs.keys()
dict_keys(['countries', 'leagues', 'matches', 'players', 'player_attributes', 'teams', 'team_attributes', 'sqlite_sequences', 'players_and_attr', 'players_in_2016', 'leagues_by_countries', 'matches_with_less_attr', 'leagues_and_matches'])
def viz_matchday_squads(matches_df=db.dfs['matches'], players_df = db.dfs["players"],
team_df = db.dfs['teams'], league_id = 1729, match_api_id = 489051):
r"""
This method is used to get all the data needed to visualize the arena, teams players and strategies of each team
"""
match_details = matches_df[matches_df['match_api_id'] == match_api_id]
# print(match_details)
# Position of the GK is set to (1,1) in the dataset which is incorrect
match_details['home_player_X1'] = 5
match_details['home_player_Y1'] = 0
match_details['away_player_X1'] = 5
match_details['away_player_Y1'] = 0
home_x_coordinates, home_y_coordinates = [], []
away_x_coordinates, away_y_coordinates = [], []
home_players, away_players = [], []
# Obtain the coordinates to denote each player's position on the field
for i in range(1, 12):
home_player_x_coordinate = 'home_player_X%d' % i
home_player_y_coordinate = 'home_player_Y%d' % i
away_player_x_coordinate = 'away_player_X%d' % i
away_player_y_coordinate = 'away_player_Y%d' % i
home_x_coordinates.append(match_details[home_player_x_coordinate].iloc[0])
home_y_coordinates.append((match_details[home_player_y_coordinate].iloc[0] + 15))
away_x_coordinates.append(match_details[away_player_x_coordinate].iloc[0])
away_y_coordinates.append((match_details[away_player_y_coordinate].iloc[0] + 35))
# Obtain the players' names
home_players.append(list(players_df[players_df['player_api_id']
== match_details['home_player_%d' % i].iloc[0]]['player_name'])[0])
away_players.append(list(players_df[players_df['player_api_id']
== match_details['away_player_%d' % i].iloc[0]]['player_name'])[0])
# Names of the Teams
home_team = team_df[team_df['team_api_id'] == match_details['home_team_api_id'].iloc[0]]['team_long_name'].iloc[0]
away_team = team_df[team_df['team_api_id'] == match_details['away_team_api_id'].iloc[0]]['team_long_name'].iloc[0]
home_team, away_team
#Formations of the Teams
home_formation = np.unique(home_y_coordinates, return_counts = True)[1]
away_formation = np.unique(away_y_coordinates, return_counts = True)[1]
img_path = PATH/'arena.jpg'
# Home team in Orange
plt.figure(figsize=(20,13))
for label, x, y in zip(home_players, home_x_coordinates, home_y_coordinates):
plt.annotate(
label,
xy = (x, y), xytext = (len(label)*-4, 20),
textcoords = 'offset points',
fontsize= 15,
color = '#F2F3F4'
)
img = imread(img_path) #Background field image
plt.title(home_team, loc = 'left', fontsize = 25)
plt.title("Home Team", fontsize = 25)
formation = "Formation: "
for i in range(1,len(home_formation)):
formation = formation + str(home_formation[i]) + "-"
formation = formation[:-1]
plt.title(formation, loc = 'right', fontsize = 25)
plt.scatter(home_x_coordinates, home_y_coordinates, s = 500, color = '#F57C00', zorder = 2)
plt.imshow(scipy.ndimage.rotate(img, 270), zorder = 1, extent=[min(home_x_coordinates)-1, max(home_x_coordinates)+1, min(home_y_coordinates)-1, max(home_y_coordinates)+1.7], aspect = 'auto')
plt.gca().invert_yaxis() # Invert y axis to start with the goalkeeper at the top
# Away team in Blue
plt.figure(figsize=(20, 13))
plt.gca().invert_xaxis() # Invert x axis to have right wingers on the right
for label, x, y in zip(away_players, away_x_coordinates, away_y_coordinates):
plt.annotate(
label,
xy = (x, y), xytext = (len(label)*-4, -30),
textcoords = 'offset points',
fontsize= 15,
color = '#F2F3F4'
)
img = imread(img_path)
plt.title(away_team, loc = 'left', fontsize = 25)
plt.title("Away Team", fontsize = 25)
formation = "Formation: "
for i in range(1,len(away_formation)):
formation = formation + str(away_formation[i]) + "-"
formation = formation[:-1]
plt.title(formation, loc = 'right', fontsize = 25)
plt.scatter(away_x_coordinates, away_y_coordinates, s = 500, color = '#0277BD', zorder = 2)
plt.imshow(scipy.ndimage.rotate(img, 270), zorder = 1, extent=[min(away_x_coordinates)-1, max(away_x_coordinates)+1, min(away_y_coordinates)-1, max(away_y_coordinates)+1.6], aspect = 'auto')
plt.show()
viz_matchday_squads()
viz_matchday_squads(league_id=24558, match_api_id=1992095)
Is there a statistical difference in the odds of winning a game when a team is playing in front of their home crowd?¶ H0 (Null Hypothesis): mean_win_rate_home = mean_win_rate_away there is no statistically significant difference in the odds of winning a game when a team is at playing at home vs. when a team is playing away HA (Alternative Hypothesis): mean_win_rate_home != mean_win_rate_away
there is a statistically significant difference in the odds of winning a game when a team is playing at home vs. when a team is playing away Alpha = 0.05
Assumptions for a 2-sample T-test: Data is collected randomly Data is independent Data is approximately normally distributed
db.dfs.keys()
dict_keys(['countries', 'leagues', 'matches', 'players', 'player_attributes', 'teams', 'team_attributes', 'sqlite_sequences', 'players_and_attr', 'players_in_2016', 'leagues_by_countries', 'matches_with_less_attr', 'leagues_and_matches'])
matches_df = db.dfs['matches']
matches_df['home_team_win'] = np.zeros
matches_df['away_team_win'] = np.zeros
# Home Team Values
#WIN
matches_df['home_team_win'].loc[matches_df['home_team_goal'] > matches_df['away_team_goal']] = 1
#LOSS
matches_df['home_team_win'].loc[matches_df['home_team_goal'] < matches_df['away_team_goal']] = 0
#TIE
matches_df['home_team_win'].loc[matches_df['home_team_goal'] == matches_df['away_team_goal']] = 0
# Away Team Values
#WIN
matches_df['away_team_win'].loc[matches_df['home_team_goal'] < matches_df['away_team_goal']] = 1
#LOSS
matches_df['away_team_win'].loc[matches_df['home_team_goal'] > matches_df['away_team_goal']] = 0
#TIE
matches_df['away_team_win'].loc[matches_df['home_team_goal'] == matches_df['away_team_goal']] = 0
#create numpy arrays
home_team_win_array = np.array(matches_df['home_team_win'])
away_team_win_array = np.array(matches_df['away_team_win'])
#the means of each array represent the win rate: win rate = matches won / matches NOT won (tie or loss)
x_bar_home = np.mean(home_team_win_array)
x_bar_away = np.mean(away_team_win_array)
#calculate the difference between the means, using all rows in the dataset
diff = x_bar_home - x_bar_away
diff
0.17133069017283187
len(home_team_win_array), len(away_team_win_array)
(25979, 25979)
n_home = len(home_team_win_array)
n_away = len(away_team_win_array)
home_wins = sum(home_team_win_array)
away_wins = sum(away_team_win_array)
home_win_rate = home_wins/n_home
away_win_rate = away_wins/n_home
diff = home_win_rate-away_win_rate
print(f"Home Win Rate: {home_win_rate} \nAway Win Rate: {away_win_rate} \nDifference: {diff}")
Home Win Rate: 0.45871665576042187 Away Win Rate: 0.28738596558759 Difference: 0.17133069017283187
var_home = home_team_win_array.var()
var_away = away_team_win_array.var()
var_home, var_away
(0.24829568548839653, 0.20479527237087852)
# TODO: Cohen's d: Effect Size
pooled_var = (n_home * var_home + n_away * var_away) / (n_home + n_away)
cohens_d = (diff) / np.sqrt(pooled_var)
cohens_d
0.35996267005447524
# Initialize parameters
effect = cohens_d
alpha = 0.05
power = 0.95
# sample 2 / sample 1
ratio = len(away_team_win_array) / len(home_team_win_array)
# Perform power analysis
analysis = TTestIndPower()
result = analysis.solve_power(effect, power=power, nobs1=None,ratio=ratio, alpha=alpha)
print(f"The minimum sample size: {result}")
print(f"Number of matches played: {len(away_team_win_array)}")
The minimum sample size: 201.5427376165529 Number of matches played: 25979
sample_means_home = []
for _ in range(1000):
sample_mean = np.random.choice(home_team_win_array, size=202).mean()
sample_means_home.append(sample_mean)
sample_means_away = []
for _ in range(1000):
sample_mean = np.random.choice(away_team_win_array, size=202).mean()
sample_means_away.append(sample_mean)
len(sample_means_home), len(sample_means_away)
(1000, 1000)
sample_means_home[:10], sample_means_away[:10]
([0.4504950495049505, 0.4405940594059406, 0.3910891089108911, 0.4900990099009901, 0.504950495049505, 0.47029702970297027, 0.45544554455445546, 0.43564356435643564, 0.43564356435643564, 0.4752475247524752], [0.297029702970297, 0.2524752475247525, 0.297029702970297, 0.2722772277227723, 0.2871287128712871, 0.3217821782178218, 0.30198019801980197, 0.297029702970297, 0.297029702970297, 0.26732673267326734])
def calc_variance(sample):
'''Computes the variance a list of values'''
sample_mean = np.mean(sample)
return sum([(i - sample_mean)**2 for i in sample])
def calc_sample_variance(sample1, sample2):
'''Computes the pooled variance 2 lists of values, using the calc_variance function'''
n_1, n_2 = len(sample1), len(sample2)
var1, var2 = calc_variance(sample1), calc_variance(sample2)
return (var1 + var2) / ((n_1 + n_2) - 2)
def calc_twosample_tstatistic(expr, ctrl):
'''Computes the 2-sample T-stat of 2 lists of values, using the calc_sample_variance function'''
expr_mean, ctrl_mean = np.mean(expr), np.mean(ctrl)
n_e, n_c = len(expr), len(ctrl)
samp_var = calc_sample_variance(expr,ctrl)
t = (expr_mean - ctrl_mean) / np.sqrt(samp_var * ((1/n_e)+(1/n_c)))
return t
t_stat = calc_twosample_tstatistic(sample_means_home, sample_means_away)
t_stat
113.3472736492802
stats.ttest_ind(sample_means_home, sample_means_away)
Ttest_indResult(statistic=113.34727364928037, pvalue=0.0)
sns.set(color_codes=True)
sns.set(rc={'figure.figsize':(12,10)})
plt.title('Bootstrapped Win Rate Frequencies', fontsize='25')
plt.xlabel('Win Rate', fontsize='20')
plt.ylabel('Win Rate Frequency', fontsize='20')
sns.distplot(sample_means_home, label='Home Win Rates') # Blue distribution
sns.distplot(sample_means_away, label='Away Win Rates') # Orange distribution
plt.legend()
plt.show()
def visualize_t(t_stat, n_control, n_experimental):
# initialize a matplotlib "figure"
fig = plt.figure(figsize=(8,5))
ax = fig.gca()
# generate points on the x axis between -20 and 20:
xs = np.linspace(-20, 20, 500)
# use stats.t.pdf to get values on the probability density function for the t-distribution
ys= stats.t.pdf(xs, (n_control+n_experimental-2), 0, 1)
ax.plot(xs, ys, linewidth=3, color='darkred')
ax.axvline(t_stat, color='black', linestyle='--', lw=5)
ax.axvline(-t_stat, color='black', linestyle='--', lw=5)
plt.xlabel('t-stat', fontsize='20')
plt.ylabel('probability density', fontsize='20')
plt.title('Probability Density of t-test',fontsize='25')
plt.show()
return None
n_home = len(home_team_win_array)
n_away = len(away_team_win_array)
visualize_t(t_stat, n_home, n_away)
## Calculate p_value manually
# Lower tail comulative density function returns area under the lower tail curve
df = len(sample_means_home)+len(sample_means_home)-2
tail = stats.t.cdf(-t_stat, df, 0, 1)
p_value = tail*2
print(p_value)
0.0
#DOUBLE CHECK WITH SCIPY
stats.t.sf(abs(t_stat), len(sample_means_home)+len(sample_means_away)-2)*2
0.0
#TRIPLE CHECK WITH SCIPY
stats.ttest_ind(sample_means_home, sample_means_away)
Ttest_indResult(statistic=113.34727364928037, pvalue=0.0)
result = pd.merge(matches_df,
db.dfs['teams'][['team_long_name','team_api_id']],
left_on='home_team_api_id',
right_on='team_api_id',
how='left')
result.rename(columns={"team_long_name": "home_team_name"}, inplace=True)
result = result.drop(columns='team_api_id')
results = pd.merge(result,
db.dfs['teams'][['team_long_name','team_api_id']],
left_on='away_team_api_id',
right_on='team_api_id',
how='left')
results.rename(columns={"team_long_name": "away_team_name"}, inplace=True)
results = results.drop(columns='team_api_id')
results['winning_team'] = np.nan
results.head()
| id | country_id | league_id | season | stage | date | match_api_id | home_team_api_id | away_team_api_id | home_team_goal | ... | GBD | GBA | BSH | BSD | BSA | home_team_win | away_team_win | home_team_name | away_team_name | winning_team | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 1 | 1 | 1 | 2008/2009 | 1 | 2008-08-17 00:00:00 | 492473 | 9987 | 9993 | 1 | ... | 3.25 | 4.00 | 1.73 | 3.40 | 4.20 | 0 | 0 | KRC Genk | Beerschot AC | NaN |
| 1 | 2 | 1 | 1 | 2008/2009 | 1 | 2008-08-16 00:00:00 | 492474 | 10000 | 9994 | 0 | ... | 3.25 | 3.75 | 1.91 | 3.25 | 3.60 | 0 | 0 | SV Zulte-Waregem | Sporting Lokeren | NaN |
| 2 | 3 | 1 | 1 | 2008/2009 | 1 | 2008-08-16 00:00:00 | 492475 | 9984 | 8635 | 0 | ... | 3.20 | 2.50 | 2.30 | 3.20 | 2.75 | 0 | 1 | KSV Cercle Brugge | RSC Anderlecht | NaN |
| 3 | 4 | 1 | 1 | 2008/2009 | 1 | 2008-08-17 00:00:00 | 492476 | 9991 | 9998 | 5 | ... | 3.75 | 5.50 | 1.44 | 3.75 | 6.50 | 1 | 0 | KAA Gent | RAEC Mons | NaN |
| 4 | 5 | 1 | 1 | 2008/2009 | 1 | 2008-08-16 00:00:00 | 492477 | 7947 | 9985 | 1 | ... | 3.50 | 1.65 | 4.75 | 3.30 | 1.67 | 0 | 1 | FCV Dender EH | Standard de Liège | NaN |
5 rows × 120 columns
results['winning_team'].loc[results['home_team_goal'] > results['away_team_goal']] = results['home_team_name']
results['winning_team'].loc[results['home_team_goal'] < results['away_team_goal']] = results['away_team_name']
results.head()
| id | country_id | league_id | season | stage | date | match_api_id | home_team_api_id | away_team_api_id | home_team_goal | ... | GBD | GBA | BSH | BSD | BSA | home_team_win | away_team_win | home_team_name | away_team_name | winning_team | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 1 | 1 | 1 | 2008/2009 | 1 | 2008-08-17 00:00:00 | 492473 | 9987 | 9993 | 1 | ... | 3.25 | 4.00 | 1.73 | 3.40 | 4.20 | 0 | 0 | KRC Genk | Beerschot AC | NaN |
| 1 | 2 | 1 | 1 | 2008/2009 | 1 | 2008-08-16 00:00:00 | 492474 | 10000 | 9994 | 0 | ... | 3.25 | 3.75 | 1.91 | 3.25 | 3.60 | 0 | 0 | SV Zulte-Waregem | Sporting Lokeren | NaN |
| 2 | 3 | 1 | 1 | 2008/2009 | 1 | 2008-08-16 00:00:00 | 492475 | 9984 | 8635 | 0 | ... | 3.20 | 2.50 | 2.30 | 3.20 | 2.75 | 0 | 1 | KSV Cercle Brugge | RSC Anderlecht | RSC Anderlecht |
| 3 | 4 | 1 | 1 | 2008/2009 | 1 | 2008-08-17 00:00:00 | 492476 | 9991 | 9998 | 5 | ... | 3.75 | 5.50 | 1.44 | 3.75 | 6.50 | 1 | 0 | KAA Gent | RAEC Mons | KAA Gent |
| 4 | 5 | 1 | 1 | 2008/2009 | 1 | 2008-08-16 00:00:00 | 492477 | 7947 | 9985 | 1 | ... | 3.50 | 1.65 | 4.75 | 3.30 | 1.67 | 0 | 1 | FCV Dender EH | Standard de Liège | Standard de Liège |
5 rows × 120 columns
home_team_win_df = results.groupby("home_team_name").agg({
"home_team_win": "mean",
})
home_team_win_df.sort_values(by= 'home_team_win',ascending=False)
| home_team_win | |
|---|---|
| home_team_name | |
| FC Barcelona | 0.861842 |
| Real Madrid CF | 0.848684 |
| SL Benfica | 0.822581 |
| FC Porto | 0.822581 |
| FC Bayern Munich | 0.801471 |
| ... | ... |
| DSC Arminia Bielefeld | 0.117647 |
| AC Arles-Avignon | 0.105263 |
| Dunfermline Athletic | 0.052632 |
| Córdoba CF | 0.052632 |
| SpVgg Greuther Fürth | 0.000000 |
296 rows × 1 columns
away_team_win_df = results.groupby("away_team_name").agg({
"away_team_win": "mean",
})
away_team_win_df.sort_values(by= 'away_team_win',ascending=False)
| away_team_win | |
|---|---|
| away_team_name | |
| Rangers | 0.684211 |
| FC Barcelona | 0.677632 |
| SL Benfica | 0.669355 |
| FC Porto | 0.653226 |
| Real Madrid CF | 0.651316 |
| ... | ... |
| CD Tenerife | 0.052632 |
| AC Arles-Avignon | 0.052632 |
| CD Numancia | 0.052632 |
| Brescia | 0.052632 |
| FC Metz | 0.052632 |
296 rows × 1 columns
plt.figure(figsize=(16,8))
plt.plot(home_team_win_df,away_team_win_df,'o', alpha = 0.4)
plt.plot([0,1],[0,1])
plt.xlabel('Home Win Rate',fontsize='20')
plt.ylabel('Away Win Rate',fontsize='20')
plt.title('Home Win Rate vs Away Win Rate',fontsize='20')
plt.xlim([0,1])
plt.ylim([0,1])
(0, 1)
db.dfs.keys()
dict_keys(['countries', 'leagues', 'matches', 'players', 'player_attributes', 'teams', 'team_attributes', 'sqlite_sequences', 'players_and_attr', 'players_in_2016', 'leagues_by_countries', 'matches_with_less_attr', 'leagues_and_matches'])
df = db.dfs['players_and_attr']
df
| player_api_id | player_name | player_fifa_api_id | birthday | height | weight | age | date | overall_rating | potential | ... | vision | penalties | marking | standing_tackle | sliding_tackle | gk_diving | gk_handling | gk_kicking | gk_positioning | gk_reflexes | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 95620 | 307224 | Kevin Koubemba | 208127 | 1993-03-23 | 193.04 | 198 | 26 | 2016-07-07 00:00:00 | 64.0 | 68.0 | ... | 55.0 | 65.0 | 22.0 | 22.0 | 25.0 | 12.0 | 12.0 | 7.0 | 11.0 | 12.0 |
| 57229 | 184521 | Florian Lejeune | 197948 | 1991-05-20 | 187.96 | 179 | 28 | 2016-07-07 00:00:00 | 73.0 | 77.0 | ... | 32.0 | 43.0 | 74.0 | 75.0 | 69.0 | 11.0 | 15.0 | 15.0 | 12.0 | 7.0 |
| 181048 | 512726 | Yanis Mbombo Lokwa | 221274 | 1994-04-08 | 177.80 | 172 | 25 | 2016-07-07 00:00:00 | 63.0 | 72.0 | ... | 48.0 | 59.0 | 15.0 | 16.0 | 12.0 | 11.0 | 12.0 | 12.0 | 12.0 | 7.0 |
| 178639 | 450002 | Wallace | 216437 | 1993-10-14 | 190.50 | 183 | 26 | 2016-07-07 00:00:00 | 74.0 | 82.0 | ... | 31.0 | 45.0 | 76.0 | 78.0 | 74.0 | 15.0 | 11.0 | 11.0 | 10.0 | 11.0 |
| 153508 | 45400 | Ronnie Schwartz | 172555 | 1989-08-29 | 182.88 | 176 | 30 | 2016-07-07 00:00:00 | 68.0 | 70.0 | ... | 45.0 | 66.0 | 23.0 | 17.0 | 23.0 | 13.0 | 11.0 | 6.0 | 9.0 | 14.0 |
| ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... |
| 77471 | 22732 | Janicio Martins | 171790 | 1979-11-30 | 180.34 | 157 | 39 | 2008-08-30 00:00:00 | 69.0 | 72.0 | ... | 44.0 | 67.0 | 72.0 | 75.0 | 59.0 | 9.0 | 23.0 | 56.0 | 23.0 | 23.0 |
| 158240 | 16368 | Savo Pavicevic | 181818 | 1980-12-11 | 185.42 | 190 | 38 | 2008-08-30 00:00:00 | 67.0 | 72.0 | ... | 64.0 | 43.0 | 71.0 | 67.0 | 64.0 | 9.0 | 21.0 | 57.0 | 21.0 | 21.0 |
| 78022 | 37976 | Jason Vandelannoite | 169170 | 1986-11-06 | 177.80 | 176 | 33 | 2008-08-30 00:00:00 | 64.0 | 68.0 | ... | 60.0 | 57.0 | 63.0 | 66.0 | 11.0 | 5.0 | 22.0 | 56.0 | 22.0 | 22.0 |
| 144773 | 359194 | Quini | 174009 | 1985-10-29 | 180.34 | 159 | 34 | 2007-08-30 00:00:00 | 56.0 | 70.0 | ... | 65.0 | 56.0 | 23.0 | 23.0 | 45.0 | 18.0 | 23.0 | 40.0 | 23.0 | 23.0 |
| 80570 | 33688 | Jeremy Gavanon | 150550 | 1983-09-20 | 182.88 | 163 | 36 | 2007-08-30 00:00:00 | 66.0 | 74.0 | ... | 54.0 | 73.0 | 25.0 | 25.0 | 53.0 | 63.0 | 67.0 | 65.0 | 64.0 | 73.0 |
10848 rows × 46 columns
def show_player_stats(name='Lionel Messi'):
# Players: 'Cristiano Ronaldo', 'Lionel Messi', 'Neymar', 'Heung-Min Son'...
player_info = db.dfs['players_and_attr']
player = player_info[player_info["player_name"] == name]
cols = ['player_name','overall_rating', 'finishing',
'heading_accuracy', 'short_passing', 'dribbling',
'sprint_speed', 'shot_power', 'jumping', 'stamina',
'strength', 'positioning', 'penalties', 'sliding_tackle']
player = player[cols]
player = player.groupby("player_name")[cols].mean().reset_index()
plt.figure(figsize=(8,8))
ax = plt.subplot(projection="polar")
cats = list(player)[1:]
N = len(cats)
mean_values = player_info.iloc[:,:].mean()
mean_values = mean_values[cols]
values = mean_values.drop("player_name").values.flatten().tolist()
values += values[:1]
angles = [n / float(N)*2* math.pi for n in range(N)]
angles += angles[:1]
plt.xticks(angles[:-1],cats,color="r",size=7)
plt.ylim([0,100])
plt.plot(angles,values,color='r',linewidth=2,linestyle="solid")
plt.fill(angles,values,color='r',alpha=1)
values = player.loc[0].drop("player_name").values.flatten().tolist()
values += values[:1]
angles = [n / float(N)*2* math.pi for n in range(N)]
angles += angles[:1]
plt.xticks(angles[:-1],cats,color="k",size=12)
plt.ylim([0,100])
plt.plot(angles,values,color='y',linewidth=3,linestyle="solid")
plt.fill(angles,values,color='y',alpha=0.5)
plt.gca().legend(('Average', name), bbox_to_anchor=(1, 0.5, 0.5, 0.5), loc=8)
plt.title(name,color="b", fontsize=18)
plt.subplots_adjust(wspace=.4,hspace=.4)
show_player_stats()
show_player_stats('Cristiano Ronaldo')
df = db.dfs['player_attributes']
df['overall_rating'].corr(df['penalties'])
0.3926222088639533
potential_features = ['acceleration', 'curve', 'free_kick_accuracy', 'ball_control', 'shot_power', 'stamina']
# check how the features are correlated with the overall ratings
for f in potential_features:
related = df['overall_rating'].corr(df[f])
print(f"{f}: {related}")
acceleration: 0.2452063826505644 curve: 0.3526143480590304 free_kick_accuracy: 0.3494238194241043 ball_control: 0.4439779241084229 shot_power: 0.4276109369596505 stamina: 0.3269068736524547
cols = ['potential', 'crossing', 'finishing', 'heading_accuracy',
'short_passing', 'volleys', 'dribbling', 'curve', 'free_kick_accuracy',
'long_passing', 'ball_control', 'acceleration', 'sprint_speed',
'agility', 'reactions', 'balance', 'shot_power', 'jumping', 'stamina',
'strength', 'long_shots', 'aggression', 'interceptions', 'positioning',
'vision', 'penalties', 'marking', 'standing_tackle', 'sliding_tackle',
'gk_diving', 'gk_handling', 'gk_kicking', 'gk_positioning',
'gk_reflexes']
# create a list containing Pearson's correlation between 'overall_rating' with each column in cols
correlations = [ df['overall_rating'].corr(df[f]) for f in cols ]
len(cols), len(correlations)
(34, 34)
# create a function for plotting a dataframe with string columns and numeric values
def plot_dataframe(df, y_label):
color='coral'
fig = plt.gcf()
fig.set_size_inches(20, 12)
plt.ylabel(y_label)
ax = df.correlation.plot(linewidth=3.3, color=color)
ax.set_xticks(df.index)
ax.set_xticklabels(df.attributes, rotation=75); #Notice the ; (remove it and see what happens !)
plt.show()
# create a dataframe using cols and correlations
df2 = pd.DataFrame({'attributes': cols, 'correlation': correlations})
# let's plot above dataframe using the function we created
plot_dataframe(df2, 'Player\'s Overall Rating')
# create a dataset containing only the birthday, date and overall_ratings from the Field Players dataset.
df = db.dfs['players_and_attr'][['birthday','date','overall_rating']]
df.head(2)
| birthday | date | overall_rating | |
|---|---|---|---|
| 95620 | 1993-03-23 | 2016-07-07 00:00:00 | 64.0 |
| 57229 | 1991-05-20 | 2016-07-07 00:00:00 | 73.0 |
# converting the birthday and date columns to date type
df['birthday'] = pd.to_datetime(df['birthday'])
df['date'] = pd.to_datetime(df['date'])
# adding a column listing the age for each row
df['age'] = df['date'].dt.year - df['birthday'].dt.year
df.head()
| birthday | date | overall_rating | age | |
|---|---|---|---|---|
| 95620 | 1993-03-23 | 2016-07-07 | 64.0 | 23 |
| 57229 | 1991-05-20 | 2016-07-07 | 73.0 | 25 |
| 181048 | 1994-04-08 | 2016-07-07 | 63.0 | 22 |
| 178639 | 1993-10-14 | 2016-07-07 | 74.0 | 23 |
| 153508 | 1989-08-29 | 2016-07-07 | 68.0 | 27 |
# finding the average ratings for each age group in the dataset
df_age_ratings = df.groupby('age').mean()
# finding the number of players in each group
df.groupby('age').count()
| birthday | date | overall_rating | |
|---|---|---|---|
| age | |||
| 17 | 9 | 9 | 9 |
| 18 | 40 | 40 | 40 |
| 19 | 164 | 164 | 164 |
| 20 | 336 | 336 | 336 |
| 21 | 437 | 437 | 437 |
| 22 | 591 | 591 | 591 |
| 23 | 598 | 598 | 598 |
| 24 | 709 | 709 | 709 |
| 25 | 748 | 748 | 748 |
| 26 | 752 | 752 | 752 |
| 27 | 771 | 771 | 771 |
| 28 | 829 | 829 | 829 |
| 29 | 786 | 786 | 786 |
| 30 | 696 | 696 | 696 |
| 31 | 640 | 640 | 640 |
| 32 | 625 | 625 | 625 |
| 33 | 545 | 545 | 545 |
| 34 | 483 | 483 | 483 |
| 35 | 431 | 431 | 431 |
| 36 | 291 | 291 | 291 |
| 37 | 165 | 165 | 165 |
| 38 | 103 | 103 | 103 |
| 39 | 36 | 36 | 36 |
| 40 | 28 | 28 | 28 |
| 41 | 22 | 22 | 22 |
| 42 | 7 | 7 | 7 |
| 43 | 4 | 4 | 4 |
| 44 | 2 | 2 | 2 |
# setting up the parameters and plotting the scatter plot
locations = df_age_ratings.index.values
height = df_age_ratings['overall_rating']
plt.style.use('ggplot')
# plotting scatter plot
plt.plot(locations, height,'-o')
# set title and labels
plt.title('Age Vs Overall Rating Relationship Chart')
plt.xlabel('Age of the players')
plt.ylabel('Overall Ratings')
plt.rcParams['figure.figsize'] = (8,6)